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  • 51.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Combined Road Prediction and Target Tracking in Collision Avoidance2004Report (Other academic)
    Abstract [en]

    Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.

  • 52.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Joint road geometry estimation and vehicle tracking: Extended version of "Combined road prediction and target tracking in collision avoidance"2004In: Proceedings of the IEEE Intelligent Vehicles Symposium, 2004, p. 619-624Conference paper (Refereed)
    Abstract [en]

    Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.

  • 53.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Obtaining Reference Road Geometry Parameters from Recorded Sensor Data2006In: Proceedings of the 2006 IEEE Intelligent Vehicles Symposium, 2006, p. 256-260Conference paper (Refereed)
    Abstract [en]

    In many applications of tracking and sensing systems, reference data for tuning and verification of system performance is unavailable. In this article the problem of automotive on-line road shape estimation is discussed and a method for obtaining reference data for this application is presented. The reference data is based on a least squares curve which is fitted geometrically to the lane boundaries. It does not require any extra sensors or other hardware. It is also shown that the accuracy of the estimate is high enough to be used as a reference in most applications.

  • 54.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pohl, Jochen
    Volvo Car Corporation, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A New Approach to Lane Guidance Systems2005In: Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 2005, p. 108-112Conference paper (Refereed)
    Abstract [en]

    This paper presents a new automotive safety function called Emergency Lane Assist (ELA). ELA combines conventional lane guidance systems with a threat assessment module that tries to activate and deactivate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure manoeuvres. Such a threat assessment algorithm is dependent on detailed information about the vehicle surroundings, i.e., positions and motion of other vehicles, but also information about road and lane geometry parameters such as lane width and road curvature. An Extended Kalman Filter for estimating these parameters is used and the performance is improved by introducing a non-linear model which uses a road aligned, curved coordinate system. The ELA decision algorithm has been tested in a demonstrator and it successfully distinguishes between dangerous and safe lane changes on a small set of test scenarios. It is also able to take control of the vehicle and put it in a safe position in the original lane.

  • 55.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pohl, Jochen
    Volvo Car Corporation, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A New Approach to Lane Guidance Systems2005Report (Other academic)
    Abstract [en]

    This paper presents a new automotive safety function called Emergency Lane Assist (ELA). ELA combines conventional lane guidance systems with a threat assessment module that tries to activate and deactivate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure manoeuvres. Such a threat assessment algorithm is dependent on detailed information about the vehicle surroundings, i.e., positions and motion of other vehicles, but also information about road and lane geometry parameters such as lane width and road curvature. An Extended Kalman Filter for estimating these parameters is used and the performance is improved by introducing a non-linear model which uses a road aligned, curved coordinate system. The ELA decision algorithm has been tested in a demonstrator and it successfully distinguishes between dangerous and safe lane changes on a small set of test scenarios. It is also able to take control of the vehicle and put it in a safe position in the original lane.

  • 56.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pohl, Jochen
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Volvo Car Corporation, Sweden.
    Joint Road Geometry Estimation and Vehicle Tracking2007Report (Other academic)
    Abstract [en]

    Detection and tracking of other vehicles and estimation of lane geometry will be required for many intelligent driver assistance systems in the future. By combining the processing of these two features into a single filter, better utilisation of the available information can be achieved. For instance, it is demonstrated that it is possible to improve the road shape estimate by including information about the lateral movement of leading vehicles. Statistical evaluation is done by comparing the estimated parameters to true values in varying road and weather conditions. The performance is also related to typical requirements of active safety applications such as adaptive cruise control and a new safety function called emergency lane assist.

  • 57.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pohl, Jochen
    Volvo Car Corporation, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Joint Road Geometry Estimation and Vehicle Tracking2007In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 15, no 12, p. 1484-1494Article in journal (Refereed)
    Abstract [en]

    Detection and tracking of other vehicles and estimation of lane geometry will be required for many intelligent driver assistance systems in the future. By combining the processing of these two features into a single filter, better utilisation of the available information can be achieved. For instance, it is demonstrated that it is possible to improve the road shape estimate by including information about the lateral movement of leading vehicles. Statistical evaluation is done by comparing the estimated parameters to true values in varying road and weather conditions. The performance is also related to typical requirements of active safety applications such as adaptive cruise control and a new safety function called emergency lane assist.

  • 58.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pohl, Jochen
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Volvo Car Corporation, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ekmark, Jonas
    Volvo Car Corporation, Sweden.
    Toward Autonomous Collision Avoidance by Steering2007Report (Other academic)
    Abstract [en]

    This paper presents a new automotive safety function called Emergency Lane Assist (ELA). ELA combines conventional lane guidance systems with a threat assessment module that tries to activate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure maneuvers. The ELA safety function is based on a statistical method that evaluates a list of safety concepts and tries to maximize the impact on accident statistics while minimizing development and hardware component costs. ELA runs in a demonstrator and successfully intervenes during lane changes that are likely to result in a collision and is also able to take control of the vehicle and return it to a safe position in the original lane. It has also been tested on 2000 km of roads in traffic without giving any false interventions

  • 59.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Pohl, Jochen
    Volvo Car Corporation, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ekmark, Jonas
    Volvo Car Corporation, Sweden.
    Toward Autonomous Collision Avoidance by Steering2007In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 8, no 1, p. 84-94Article in journal (Refereed)
    Abstract [en]

    This paper presents a new automotive safety function called Emergency Lane Assist (ELA). ELA combines conventional lane guidance systems with a threat assessment module that tries to activate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure maneuvers. The ELA safety function is based on a statistical method that evaluates a list of safety concepts and tries to maximize the impact on accident statistics while minimizing development and hardware component costs. ELA. runs in a demonstrator and successfully intervenes during lane changes that are likely to result in a collision and is also able to take control of the vehicle and return it to a safe position in the original lane. It has also been tested on 2000 km of roads in traffic without giving any false interventions.

  • 60.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Marginalized Particle Filter for Automotive Tracking Applications2005Report (Other academic)
    Abstract [en]

    This paper deals with the problem of estimating the vehicle surroundings (lane geometry and the position of other vehicles), which is needed for intelligent automotive systems, such as adaptive cruise control, collision avoidance and lane guidance. This results in a nonlinear estimation problem. For automotive tracking systems, these problems are traditionally handled using the extended Kalman filter. In this paper we describe the application of the marginalized particle filter to this problem. Studies using both synthetic and authentic data show that the marginalized particle filter can in fact give better performance than the extended Kalman filter. However, the computational load is higher.

  • 61.
    Eidehall, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Marginalized Particle Filter for Automotive Tracking Applications2005In: Proceedings of the 2005 IEEE Intelligent Vehicles Symposium, 2005, p. 370-375Conference paper (Refereed)
    Abstract [en]

    This paper deals with the problem of estimating the vehicle surroundings (lane geometry and the position of other vehicles), which is needed for intelligent automotive systems, such as adaptive cruise control, collision avoidance and lane guidance. This results in a nonlinear estimation problem. For automotive tracking systems, these problems are traditionally handled using the extended Kalman filter. In this paper we describe the application of the marginalized particle filter to this problem. Studies using both synthetic and authentic data show that the marginalized particle filter can in fact give better performance than the extended Kalman filter. However, the computational load is higher.

  • 62. Ekström, Håkan
    et al.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hardware and Software Documentation for Tire-Road Friction Estimator1993Report (Other academic)
  • 63.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Equalization of Time Errors in Time Interleaved ADC System - Part I: Theory2003Report (Other academic)
    Abstract [en]

    To significantly increase the sampling rate of an A/D converter (ADC), a time interleaved ADC system is a good option. The drawback of a time interleaved ADC system is that the ADCs are not exactly identical dueto errors in the manufacturing process. This means that time, gain and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the sampled signal. In this paper we present a method for estimation and compensation of the time mismatch errors. The estimation method requires no knowledge about the input signal except that it should be band limited to the Nyquist frequency for the complete ADC system. This means that the errors can be estimated whilethe ADC is running. The method is also adaptive to slow changes in the time errors.

  • 64.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    Infineon, Sweden.
    Amplitude and Gain Error Influence on Time Error Estimation Algorithm for Time Interleaved A/D Converter System2001Report (Other academic)
    Abstract [en]

    A method for blind estimation of static time errors in time interleaved A/D converters is investigated. The method assumes tha tamplitude and gain errors are removed before the time error estimation. Even if the amplitude and gain errors are estimated and removed, there will be small errors left. In this paper, we investigate how the amplitude and gain errors influence the time error estimation performance.

  • 65.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    Infineon, Sweden.
    Amplitude and Gain Error Influence on Time Error Estimation Algorithm for Time Interleaved A/D Converter System2002In: Proceedings of the 2002 IEEE International Conference on Acoustics, Speech and Signal Processing, 2002, p. 1281-Conference paper (Refereed)
    Abstract [en]

    A method for blind estimation of static time errors in time interleaved A/D converters is investigated. The method assumes tha tamplitude and gain errors are removed before the time error estimation. Even if the amplitude and gain errors are estimated and removed, there will be small errors left. In this paper, we investigate how the amplitude and gain errors influence the time error estimation performance.

  • 66.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    Infineon, Sweden.
    Analysis of Mismatch Effects in Randomly Interleaved A/D Converter System2003Report (Other academic)
    Abstract [en]

    To significantly increase the sampling rate of an A/D converter (ADC), a time interleaved ADC system is a good option. The drawback of a time interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain and offset mismatch errors are introduced in the ADC system. These errors cause non harmonic distortion in the sampled signal. One way to decrease the impact of the mismatch errors is to spread the distortion over a wider frequency range by randomizing the order in which the ADCs are used in the interleaved structure. In this paper we analyze how the spectrum is affected by mismatch errors in a randomly interleaved ADC system. We also discuss how the mismatch errors can be estimated.

  • 67.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    Infineon, Sweden.
    Analysis of Mismatch Noise in Randomly Interleaved ADC Systems2003In: Proceedings of the 2003 IEEE International Conference on Acoustics, Speech and Signal Processing, 2003, p. 277-280 vol.6Conference paper (Refereed)
    Abstract [en]

    Time interleaved A/D converters (ADC) can be used to increase the sample rate of an ADC system. However, a problem with time interleaved ADC is that distortion is introduced in the output signal due to various mismatch errors between the ADC. One way to decrease the impact of the mismatch errors is to introduce additional ADC in the interleaved structure and randomly select an ADC at each sample instance. The periodicity of the errors is then removed and the spurious distortion is changed to a more noiselike distortion, spread over the whole spectrum. In this paper, a probabilistic model of the randomly interleaved ADC system is presented. The noise spectrum caused by gain errors is also analyzed.

  • 68.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    Infineon, Sweden.
    Blind Adaptive Equalization of Mismatch Errors in Time Interleaved A/D Converter System2003Report (Other academic)
    Abstract [en]

    To significantly increase the sampling rate of an AID converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the sampled signal. In this paper, we present a method for estimation and compensation of the mismatch errors. The estimation method requires no knowledge about the input signal except that it should be bandlimited to the Nyquist frequency for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the mismatch errors. The estimation method has been validated with simulations and measurements from a time-interleaved ADC system.

  • 69.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    Infineon, Sweden.
    Blind Adaptive Equalization of Mismatch Errors in Time Interleaved A/D Converter System2004In: IEEE Transactions on Circuits And Systems Part I: Fundamental Theory and Applications, ISSN 1057-7122, E-ISSN 1558-1268, Vol. 51, no 1, p. 151-158Article in journal (Refereed)
    Abstract [en]

    To significantly increase the sampling rate of an AID converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the sampled signal. In this paper, we present a method for estimation and compensation of the mismatch errors. The estimation method requires no knowledge about the input signal except that it should be bandlimited to the Nyquist frequency for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the mismatch errors. The estimation method has been validated with simulations and measurements from a time-interleaved ADC system.

  • 70.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik
    infineon, Sweden.
    Equalization of Time Errors in Time Interleaved ADC System - Part II: Analysis and Examples2003Report (Other academic)
    Abstract [en]

    In the accompanying paper a method for blind (i.e., no calibration needed) estimation and compensation of the time errors in a time interleaved ADC system was presented. In this paper we evaluate this method. The Cramer-Rao bound is calculated, both for additive noise and random clock jitter. Monte-Carlo simulations have also been done to compare to the CRB. Finally, the estimation method is validated on measurements from areal time interleaved ADC system with 16 ADCs.

  • 71.
    Elbornsson, Jonas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Eklund, Jan-Erik Eklund
    Infineon, Sweden.
    Analysis of Mismatch Effects in Randomly Interleaved A/D Converter System2005In: IEEE Transactions on Circuits And Systems Part I: Fundamental Theory and Applications, ISSN 1057-7122, E-ISSN 1558-1268, Vol. 52, no 3, p. 465-476Article in journal (Refereed)
    Abstract [en]

    To significantly increase the sampling rate of an A/D converter (ADC), a time interleaved ADC system is a good option. The drawback of a time interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain and offset mismatch errors are introduced in the ADC system. These errors cause non harmonic distortion in the sampled signal. One way to decrease the impact of the mismatch errors is to spread the distortion over a wider frequency range by randomizing the order in which the ADCs are used in the interleaved structure. In this paper we analyze how the spectrum is affected by mismatch errors in a randomly interleaved ADC system. We also discuss how the mismatch errors can be estimated.

  • 72.
    Elbornsson, Jonas
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Gustafsson, Fredrik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control.
    Eklund, JE
    Blind equalization of time errors in a time-interleaved ADC system2005In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 53, no 4, p. 1413-1424Article in journal (Refereed)
    Abstract [en]

    To significantly increase the sampling rate of an analog-to-digital converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the sampled signal. In this paper, we present a method for estimation and compensation of the time mismatch errors. The estimation method requires no knowledge about the input signal, except that it should be band limited to the foldover frequency pi/T-s for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the time errors. The Cramer-Rao bound (CRB) for the time error estimates is also calculated and compared. to Monte Carlo simulations. The estimation method has also been validated on measurements from a real time-interleaved ADC system with 16 ADCs.

  • 73.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Bias Compensated Least Squares Estimation of Continuous Time Output Error Models in the Case of Stochastic Sampling Time Jitter2006In: Proceedings of the 14th IFAC Symposium on System Identification, 2006, p. 612-617Conference paper (Refereed)
    Abstract [en]

    This work investigates how stochastic unmeasureable sampling jitternoise affects the result of system identification, and proposes a modification ofknown approaches to mitigate the effects of sampling jitter. By just assumingconventional additive measurement noise, the analysis shows that the identifiedmodel will get a bias in the transfer function amplitude that increases for higherfrequencies. A frequency domain approach with a continuous time system modelallows an analysis framework for sampling jitter noise. This leads to a biascompensated (weighted) least squares algorithm. A continuous time output errormodel is used for numerical illustration.

  • 74.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Downsampling Non-Uniformly Sampled Data2007Report (Other academic)
    Abstract [en]

    Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with normalized cutoff frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate non-uniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the inter-sample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process.

  • 75.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Downsampling Non-Uniformly Sampled Data2008In: EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, E-ISSN 1687-6180Article in journal (Refereed)
    Abstract [en]

    Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with normalized cutoff frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate non-uniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the inter-sample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process.

  • 76.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Analysis using Non-Uniform Sampling with Application to Active Queue Management, Extended2004In: Proceedings of Reglermöte 2004, 2004Conference paper (Other academic)
    Abstract [en]

    In many real-time applications, sample values and time stamps are delivered in pairs, where sampling times are non-uniform. Frequency analysis using non-uniform data occurs in various real life problems and embedded systems, such as vibrational analysis in cars and control of packet network queue lengths. Our contribution is to first overview different ways to approximate the Fouirer transform, and secondly to give analytical expressions for how non-uniform sampling affects these approximations. The results are expressed in terms of frequency windows describing how a single frequency in the continuous time signal is smeared out in the frequency domain, or, more precisely, in the expected value of the Fourier transform approximation.

  • 77.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Analysis using Non-Uniform Sampling with Application to Active Queue Management, Extended2004In: Proceedings of the 5th Conference on Computer Science and Systems Engineering, 2004, p. 147-151Conference paper (Other academic)
    Abstract [en]

    In many real-time applications, sample values and time stamps are delivered in pairs, where sampling times are non-uniform. Frequency analysis using non-uniform data occurs in various real life problems and embedded systems, such as vibrational analysis in cars and control of packet network queue lengths. Our contribution is to first overview different ways to approximate the Fourier transform, and secondly to give analytical expressions for how non-uniform sampling affects these approximations. The results are expressed in terms of frequency windows describing how a single frequency in the continuous time signal is smeared out in the frequency domain, or, more precisely, in the expected value of the Fourier transform approximation.

  • 78.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Transforms based on Nonuniform Sampling - Basic Stochastic Properties2005In: Proceedings of Radiovetenskap och kommunikation 2005, 2005Conference paper (Other academic)
    Abstract [en]

    We investigate two natural linear estimates of a signal's continuous time Fourier transform (FT) based on non-uniform samples, where sample value and sample time come in pairs where at least the sampling time is a stochastic process. Such stochastic sampling occurs in several applications, such as queue theory and event based sampling. Analytical expressions of mean and covariance are derived for the FT estimate. Intended use of these are to give uncertainty bounds on transforms and spectral estimates, but they are also useful in signal estimation and system identication.

  • 79.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Transforms based on Nonuniform Sampling - Basic Stochastic Properties2004Report (Other academic)
    Abstract [en]

    We investigate two natural linear estimates of a signal's continuous time Fourier transform (FT) based on non-uniform samples, where sample value and sample time come in pairs where at least the sampling time is a stochastic process. Such stochastic sampling occurs in several applications, such as queue theory and event based sampling. Analytical expressions of mean and covariance are derived for the FT estimate. Intended use of these are to give uncertainty bounds on transforms and spectral estimates, but they are also useful in signal estimation and system identication.

  • 80.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification with Stochastic Sampling Time Jitter2006Report (Other academic)
    Abstract [en]

    This work investigates how stochastic sampling jitter noise affects the result of system identification, and proposes a modification of known approaches to mitigate the effects of sampling jitter, when the jitter is unknown and not directly measurable. By just assuming conventional additive measurement noise, the analysis shows that the identified model will get a bias in the transfer function amplitude that increases for higher frequencies. A frequency domain approach with a continuous-time model allows an analysis framework for sampling jitter noise. The bias and covariance in the frequency domain model are derived. These are used in bias compensated (weighted) least squares algorithms, and by asymptotic arguments this leads to a maximum likelihood algorithm. Continuous-time output error models are used for numerical illustrations.

  • 81.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification with Stochastic Sampling Time Jitter2008In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 44, no 3, p. 637-646Article in journal (Refereed)
    Abstract [en]

    This work investigates how stochastic sampling jitter noise affects the result of system identification, and proposes a modification of known approaches to mitigate the effects of sampling jitter, when the jitter is unknown and not directly measurable. By just assuming conventional additive measurement noise, the analysis shows that the identified model will get a bias in the transfer function amplitude that increases for higher frequencies. A frequency domain approach with a continuous-time model allows an analysis framework for sampling jitter noise. The bias and covariance in the frequency domain model are derived. These are used in bias compensated (weighted) least squares algorithms, and by asymptotic arguments this leads to a maximum likelihood algorithm. Continuous-time output error models are used for numerical illustrations.

  • 82.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    System Identification using Measurements Subject to Stochastic Time Jitter2005In: Proceedings of the 16th IFAC World Congress, 2005, p. 197-197Conference paper (Refereed)
    Abstract [en]

    When the sensors readings are perturbed by an unknown stochastic time jitter, classical system identification algorithms based on additive amplitude perturbations will give biased estimates. We here outline the maximum likelihood procedure, for the case of both time and amplitude noise, in the frequency domain, based on the measurement DFT. The method directly applies to output error continuous time models, while a simple sinusoid in noise example is used to illustrate the bias removal of the proposed method.

  • 83.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    System Identification using Measurements Subject to Stochastic Time Jitter2004Report (Other academic)
    Abstract [en]

    When the sensors readings are perturbed by an unknown stochastic time jitter, classical system identification algorithms based on additive amplitude perturbations will give biased estimates. We here outline the maximum likelihood procedure, for the case of both time and amplitude noise, in the frequency domain, based on the measurement DFT. The method directly applies to output error continuous time models, while a simple sinusoid in noise example is used to illustrate the bias removal of the proposed method.

  • 84.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Analysis using Non-Uniform Sampling with Application to Active Queue Management2004In: Proceedings of the 2004 IEEE International Conference on Acoustics, Speech and Signal Processing, 2004, p. 581-584Conference paper (Refereed)
    Abstract [en]

    In many real-time applications, sample values and time stamps are delivered in pairs, where sampling times are non-uniform. Frequency analysis using non-uniform data occurs in various real life problems and embedded systems, such as vibrational analysis in cars and control of packet network queue lengths. Our contribution is to first overview different ways to approximate the Fourier transform, and secondly to give analytical expressions for how non-uniform sampling affects these approximations. The results are expressed in terms of frequency windows describing how a single frequency in the continuous time signal is smeared out in the frequency domain, or, more precisely, in the expected value of the Fourier transform approximation.

  • 85.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Domain Analysis of Signals with Stochastic Sampling Times2007Report (Other academic)
    Abstract [en]

    In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several methods to compute an approximate Fourier transform (AFT) have appeared in literature, and their posterior properties in terms of alias suppression and leakage have been addressed. In this paper, the sampling times are assumed to be generated by a stochastic process. The main result gives the prior distribution of several AFTs expressed in terms of the true Fourier transform and variants of the characteristic function of the sampling time distribution. The result extends leakage and alias suppression with bias and variance terms due to NUS. Specific sampling processes as described in literature are analyzed in detail. The results are illustrated on simulated signals, with particular focus to the implications for spectral estimation.

  • 86.
    Eng, Frida
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frequency Domain Analysis of Signals with Stochastic Sampling Times2008In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, no 7, p. 3089-3099Article in journal (Refereed)
    Abstract [en]

    In nonuniform sampling (NUS), signal amplitudes and time stamps are delivered in pairs. Several methods to compute an approximate Fourier transform (AFT) have appeared in literature, and their posterior properties in terms of alias suppression and leakage have been addressed. In this paper, the sampling times are assumed to be generated by a stochastic process. The main result gives the prior distribution of several AFTs expressed in terms of the true Fourier transform and variants of the characteristic function of the sampling time distribution. The result extends leakage and alias suppression with bias and variance terms due to NUS. Specific sampling processes as described in literature are analyzed in detail. The results are illustrated on simulated signals, with particular focus to the implications for spectral estimation.

  • 87.
    Evestedt, Niclas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Axehill, Daniel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Trincavelli, Marco
    Research and Development, Scania CV AB, Södertälje, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Sampling Recovery for Closed Loop Rapidly Expanding Random Tree using Brake Profile Regeneration2015In: Intelligent Vehicles Symposium (IV), 2015 IEEE, IEEE , 2015, p. 101-106Conference paper (Refereed)
    Abstract [en]

    In this paper an extension to the sampling based motion planning framework CL-RRT is presented. The framework uses a system model and a stabilizing controller to sample the perceived environment and build a tree of possible trajectories that are evaluated for execution. Complex system models and constraints are easily handled by a forward simulation making the framework widely applicable. To increase operational safety we propose a sampling recovery scheme that performs a deterministic brake profile regeneration using collision information from the forward simulation. This greatly increases the number of safe trajectories and also reduces the number of samples that produce infeasible results. We apply the framework to a Scania G480 mining truck and evaluate the algorithm in a simple yet challenging obstacle course and show that our approach greatly increases the number of feasible paths available for execution.

  • 88.
    Feng, Yin
    et al.
    Technical University, Darmstadt, Germany.
    Ang, Li
    Technical University Darmstadt, Germany.
    Zoubir, Abdelhak M.
    Technical University Darmstadt, Germany.
    Fritsche, Carsten
    IFEN GmbH, Poing, Germany.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    RSS-based sensor network localization in contaminated Gaussian measurement noise2013In: IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013, IEEE , 2013, p. 121-124Conference paper (Refereed)
    Abstract [en]

    We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

  • 89.
    Forsling, Robin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Sjanic, Zoran
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Consistent Distributed Track Fusion Under Communication Constraints2019In: Proceedings of the 22nd International Conference on Information Fusion (FUSION), 2019Conference paper (Refereed)
    Abstract [en]

    This paper addresses the problem of retrieving consistentestimates in a distributed network where the communication between the nodes is constrained such that only the diagonal elements of the covariance matrix are allowed to be exchanged. Several methods are developed for preserving and/or recovering consistency under the constraints imposed by the communication protocol. The proposed methods are used in conjunction with the covariance intersection method and the estimation performance is evaluated based on information usage and consistency. The results show that among the proposed methods, consistency can be preserved equally well at the transmitting node as at the receiving node.

  • 90.
    Forssell, Urban
    et al.
    NIRA Dynamics AB, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ahlqvist, Stefan
    NIRA Dynamics AB.
    Hall, Peter
    NIRA Dynamics AB.
    Map-Aided Positioning System2002In: Proceedings of FISITA 2002 World Automotive Congress, 2002Conference paper (Refereed)
    Abstract [en]

    This paper describes the vehicle positioning system MAP (Map-Aided Positioning) developed by NIRA Dynamics AB. MAP uses sensor fusion to combine relative position information from the wheel speed sensors with digital map information, and is capable of computing an accurate estimate of a vehicle’s absolute position without support from GPS or other external positioning service. MAP can also be combined with GPS, in which case a very robust andaccurate positioning system is obtained. MAP is available as a software module suitable for integration in a PDA or similar hardware platform

  • 91.
    Forssell, Urban
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    McKelvey, Tomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Time-Domain Identification of Dynamic Errors-in-Variables Systems using Period Excitation Signals1999In: Proceedings of the 14th IFAC World Congress, 1999, p. 421-426Conference paper (Refereed)
    Abstract [en]

    The use of periodic excitation signals in identification experiments is advocated. With periodic excitation it is possible to separate the driving signals and the disturbances, which for instance implies that the noise properties can be independently estimated. In the paper a non-parametric noise model, estimated directly from the measured data, is used in a compensation strategy applicable to both least squares and total least squares estimation. The resulting least squares and total least squares methods are applicable in the errors-in-variables situation and give consistent estimates regardless of the noise. The feasibility of the idea is illustrated in a simulation study.

  • 92.
    Forssell, Urban
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    McKelvey, Tomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Time-Domain Identification of Dynamic Errors-in-Variables Systems Using Periodic Excitation Signals1998Report (Other academic)
    Abstract [en]

    The use of periodic excitation signals in identification experiments is advocated. With periodic excitation it is possible to separate the driving signals and the disturbances, which for instance implies that the noise properties can be independently estimated. In the paper a non-parametric noise model, estimated directly from the measured data, is used in a compensation strategy applicable to both least squares and total least squares estimation. The resulting least squares and total least squares methods are applicable in the errors-in-variables situation and give consistent estimates regardless of the noise. The feasibility of the idea is illustrated in a simulation study.

  • 93.
    Fritsche, Carsten
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    The Marginal Bayesian Cramér–Rao Bound for Jump Markov Systems2016In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 23, no 5, p. 575-579Article in journal (Refereed)
    Abstract [en]

    In this letter, numerical algorithms for computing the marginal version of the Bayesian Cramér–Rao bound (M-BCRB) for jump Markov nonlinear systems and jump Markov linear Gaussian systems are proposed. Benchmark examples for both systems illustrate that the M-BCRB is tighter than three other recently proposed BCRBs

  • 94.
    Fritsche, Carsten
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Bayesian Bhattacharyya bound for discrete-time filtering revisited2017In: Proc. of 2017 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017, p. 719-723Conference paper (Refereed)
    Abstract [en]

    In this paper, the derivation of the Bayesian Bhattacharyya bound for discrete-time filtering as proposed ina paper by Reece and Nicholson is revisited. It turns out that the results presented in the aforementioned contribution are incorrect, as some expectations appearing in the information matrix recursions are missing. This paper gives a generalized derivation of the N-th order Bayesian Bhattacharyya bound and presents corrected expressions for the case N = 2. A nonlinear toy example is used to illustrate the results

  • 95.
    Fritsche, Carsten
    et al.
    IFEN GmbH, Germany .
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Bounds on the Optimal Performance for Jump Markov Linear Gaussian Systems2013In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 1, p. 92-98Article in journal (Refereed)
    Abstract [en]

    The performance of an optimal filter is lower bounded by the Bayesian Cramer-Rao Bound (BCRB). In some cases, this bound is tight (achieved by the optimal filter) asymptotically in information, i.e., high signal-to-noise ratio (SNR). However, for jump Markov linear Gaussian systems (JMLGS) the BCRB is not necessarily achieved for any SNR. In this paper, we derive a new bound which is tight for all SNRs. The bound evaluates the expected covariance of the optimal filter which is represented by one deterministic term and one stochastic term that is computed with Monte Carlo methods. The bound relates to and improves on a recently presented BCRB and an enumeration BCRB for JMLGS. We analyze their relations theoretically and illustrate them on a couple of examples.

  • 96.
    Fritsche, Carsten
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Klein, Anja
    Fachgebiet Kommunikationstechnik, Institut für Nachrichtentechnik,Technische Universität Darmstadt, Darmstadt, Germany.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Bayesian Cramer-Rao Bound for Mobile Terminal Tracking in Mixed LOS/NLOS Environments2013In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 2, no 3, p. 335-338Article in journal (Refereed)
    Abstract [en]

    A computational algorithm is presented for the Bayesian Cramer-Rao lower bound (BCRB) in filtering applications with measurement noise from mixture distributions with jump Markov switching structure. Such mixture distributions are common for radio propagation in mixed line- and non-line-of-sight environments. The newly derived BCRB is tighter than earlier more general bounds proposed in literature, and thus gives a more realistic bound on actual estimation performance. The resulting BCRB can be used to compute a lower bound on root mean square error of position estimates in a large class of radio localization applications. We illustrate this on an archetypical tracking application using a nearly constant velocity model and time of arrival observations.

  • 97.
    Fritsche, Carsten
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Bobrovsky-Zakai Bound for Filtering, Prediction and Smoothing of Nonlinear Dynamic Systems2018In: 2018 21st International Conference on Information Fusion (FUSION), 2018, p. 1-8Conference paper (Refereed)
    Abstract [en]

    In this paper, recursive Bobrovsky-Zakai bounds for filtering, prediction and smoothing of nonlinear dynamic systems are presented. The similarities and differences to an existing Bobrovsky-Zakai bound in the literature for the filtering case are highlighted. The tightness of the derived bounds are illustrated on a simple example where a linear system with non-Gaussian measurement likelihood is considered. The proposed bounds are also compared with the performance of some well known filters/predictors/smoothers and other Bayesian bounds.

  • 98.
    Fritsche, Carsten
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Middle East Technical University, Turkey.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    On parametric lower bounds for discrete-time filtering2016In: 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 4338-4342Conference paper (Refereed)
    Abstract [en]

    Parametric Cramer-Rao lower bounds (CRLBs) are given for discrete-time systems with non-zero process noise. Recursive expressions for the conditional bias and mean-square-error (MSE) (given a specific state sequence) are obtained for Kalman filter estimating the states of a linear Gaussian system. It is discussed that Kalman filter is conditionally biased with a non-zero process noise realization in the given state sequence. Recursive parametric CRLBs are obtained for biased estimators for linear state estimators of linear Gaussian systems. Simulation studies are conducted where it is shown that Kalman filter is not an efficient estimator in a conditional sense.

  • 99.
    Fritsche, Carsten
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Orguner, Umut
    Middle East Technical University, Turkey.
    Svensson, Lennart
    Chalmers University of Technology, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Recent Results on Bayesian Cramer-Rao Bounds for Jump Markov Systems2016In: Proc. 19th International Conference on Information Fusion (FUSION), Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 512-520Conference paper (Refereed)
    Abstract [en]

    In this paper, recent results on the evaluation of the Bayesian Cramer-Rao bound for jump Markov systems are presented. In particular, previous work is extended to jump Markov systems where the discrete mode variable enters into both the process and measurement equation, as well as where it enters exclusively into the measurement equation. Recursive approximations are derived with finite memory requirements as well as algorithms for checking the validity of these approximations are established. The tightness of the bound and the validity of its approximation is investigated on a couple of examples.

  • 100.
    Fritsche, Carsten
    et al.
    IFEN GmbH, Germany .
    Orguner, Umut
    Middle E Technical University, Turkey .
    Svensson, Lennart
    Chalmers, Sweden .
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The Marginal Enumeration Bayesian Cramer-Rao Bound for Jump Markov Systems2014In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 21, no 4, p. 464-468Article in journal (Refereed)
    Abstract [en]

    A marginal version of the enumeration Bayesian Cramer-Rao Bound (EBCRB) for jump Markov systems is proposed. It is shown that the proposed bound is at least as tight as EBCRB and the improvement stems from better handling of the nonlinearities. The new bound is illustrated to yield tighter results than BCRB and EBCRB on a benchmark example.

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