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  • 1.
    Alam, Assad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Asplund, Fredrik
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Behere, Sagar
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Björk, Mattias
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Garcia Alonso, Liliana
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Khaksari, Farzad
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Khan, Altamash
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Kjellberg, Joakim
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Lyberger, Rickard
    Scania CV AB.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Pettersson, Henrik
    Scania CV AB.
    Pettersson, Simon
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Stålklinga, Elin
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Sundman, Dennis
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zachariah, Dave
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Cooperative driving according to Scoop2011Report (Other academic)
    Abstract [en]

    KTH Royal Institute of Technology and Scania are entering the GCDC 2011 under the name Scoop –Stockholm Cooperative Driving. This paper is an introduction to their team and to the technical approach theyare using in their prototype system for GCDC 2011.

  • 2.
    De Angelis, Alessio
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Nilsson, John Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Carbone, P.
    Indoor positioning by ultra wide band radio aided inertial navigation2009In: 19th IMEKO World Congress 2009, 2009, 450-455 p.Conference paper (Refereed)
    Abstract [en]

    In this paper, a research activity aimed at developing an indoor positioning system is presented. The realized system prototype uses sensor fusion techniques to combine information from two sources: a local Ultra-Wideband (UWB) radio based distance-measuring system infrastructure and an Inertial Navigation System (INS). The UWB system provides a measure of distance between two transceivers by measuring the time-of-flight of pulses. Its principle of operation is briefly described, together with the main features of its architecture. Furthermore, the main characteristics of the INS and of the Extended Kalman Filter information fusion approach are presented. Finally, some experimental results are provided, relative to static and dynamic position measurements.

  • 3.
    De Angelis, Alessio
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Carbone, Paolo
    Indoor positioning by ultra wide band radio aided inertial navigation2010In: Metrology and Measurement Systems, ISSN 0860-8229, Vol. 17, no 3, 447-460 p.Article in journal (Refereed)
    Abstract [en]

    A research study aimed at developing a novel indoor positioning system is presented. The realized system prototype uses sensor fusion techniques to combine information from two sources: an in-house developed local Ultra-Wideband (UWB) radio-based ranging system and an inertial navigation system (INS). The UWB system measures the distance between two transceivers by recording the round-trip-time (RTT) of UWB radio pulses. Its principle of operation is briefly described, together with the main design features. Furthermore, the main characteristics of the INS and of the Extended Kalman Filter information fusion approach are presented. Finally, selected static and dynamic test scenario experimental results are provided. In particular, the advantages of the proposed information fusion approach are further investigated by means of a high dynamic test scenario.

  • 4.
    De Angelis, Alessio
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    UWB Ranging Hardware Platform2010In: GigaHertz Symposium, Lund, Sweden, 2010Conference paper (Other academic)
  • 5.
    Hari, K.V.S.
    et al.
    Indian Institute of Science (IISc).
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rantakokko, Jouni
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Prateek, G.V.
    Indian Institute of Science (IISc).
    A prototype of a first-responder indoor localization system2013In: Journal of the Indian Institute of Science, ISSN 0970-4140, Vol. 93, no 3, 511-520 p.Article, review/survey (Refereed)
    Abstract [en]

    In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.

  • 6.
    Kristensen, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Analytical argument likelihood function for a noncentral bivariate symmetric Gaussian distribution2013Report (Other academic)
    Abstract [en]

    In this short report we derive an analytical likelihood function for the argument of a complex or 2D variable with a Gaussian perturbation. It is further noted that this likelihood function can be divided into an uninformative uniform part and an informative part.

  • 7.
    Kristensen, Johan
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fast triangular binning kernel approximations for weighted gradient histogram creation2014In: 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), 2014, 6740351- p.Conference paper (Refereed)
    Abstract [en]

    The implementation of weighted gradient histograms are studied. Such histograms are commonly used in computer vision methods, and their creation can make up a significant portion of the computational cost. Further, due to potentially severe aliasing, non-uniform binning kernels are desirable. We show that previously presented fast methods for uniform binning kernels can be extended to non-uniform binning, and that the triangular kernel can be well approximated for common weighting strategies. The approximation is implemented with sums and products of projections of the gradient samples on specially chosen vectors. Consequently, only a few standard arithmetic operations are required, and therefore, the suggested implementation has a significantly lower computational cost when compared with an implementation in which the gradient argument and magnitude are explicitly evaluated. Finally, the frequency components of the different kernels are studied to quantify the fundamental gain achieved by using triangular kernels instead of uniform kernels.

  • 8.
    Nilsson, John Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fast Argument Quantization2013In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 30, no 6, 169-172 p.Article in journal (Refereed)
    Abstract [en]

    Aquantized low-resolution argument of a complex number or two-dimensional vector is required in many digital signal processing algorithms. Examples include APSK code demodulation for which it may be used to evaluate the Voronoi diagram; low-level processing for many computer vision methods that exploit histograms of gradient sample arguments, e.g., SIFT and HOG; and phase tracking/frequency estimation for which it may be used as a low-cost phase approximation. Often, such quantized arguments will have to be computed many times and under real-time constraints. Therefore, efficient solutions to these calculations are of interest.

  • 9.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Efficient implementation of data binning in sectors2012Report (Other academic)
    Abstract [en]

    We analyze the implementation of data binning of $\mathbb{R}^2$-vectors or complex numbers in sectors defined by ranges of vector/complex arguments. The binning problem is formalized and 4 different equivalent formulations are given resulting in 4 different solution methods. The 4 different methods have different implementation properties making them favorable on different platforms and under different circumstances. Binning with respect to the vector/complex number magnitude is also briefly covered. All methods are presented in a common bisection framework which make them easy to compare. The methods are given in basic arithmetic operations and logics and are directly emendable for implementation for both integer, fixed and floating point data. Detailed implementation aspects and optimizations are discussed and C-code snippets are given for the different methods.

  • 10.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Infrastructure-free pedestrian localization2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Knowledge of your own and other's positions are frequently a prerequisite for acting, leading others, and interacting in and with the environment; to retrieve relevant information and to process and interpret it; and to understand, compile, and learn from observations of the surrounding and its dynamics. This holds for humans as well as for machines and systems made for supporting and controlling them. Consequently, systems which automatically provide position information of peoples are of interest and the larger subject area of this thesis. Position can be obtained from well-known infrastructure based systems such as GPS. However, these systems carry obvious drawbacks in their infrastructure dependence which gives them limited coverage and system robustness. By observing our own ability to localize ourselves, it is obvious that localization without infrastructure at with a better (relative) accuracy is achievable. The development over the last decades of sensor and processing hardware and statistical methods have started to make such localization possible. This thesis specifically concerns systems and statistical methods for infrastructure-free localization. The this primarily deals with statistical methods but also describe hardware in terms of high-level system designs.

    For many critical applications such as positioning of emergency responders, dismounted soldiers, and security personnel, it is unsuitable for the positioning system to be dependent on infrastructure or prior knowledge about the environment. Consequently, this thesis deals with systems and methods for infrastructure-free and prior-knowledge-free pedestrian localization. The thesis is specifically concerned with statistical methods but will also cover hardware in terms of high-level system designs. The thesis is composed of an introduction followed by a collection of papers which are divided into two parts, each concerning a separate problem area. The introduction motivates and describes the localization problem in general terms and gives a coherent guide to the articles.

    The first group of articles together describes an infrastructure-free system for tactical localization of small units of agents. The physical implementation of the localization system carries the name TOR (Tacitcal lOcatoR) and have been tested on fire fighters during realistic smoke diving exercises. This system primarily depends on pedestrian dead-reckoning based on foot-mounted inertial navigation and inter-agent radio ranging. The core parts of the system which are dealt with are: foot-mounted inertial navigation units which provides dead reckoning of individual agents, system structure and estimation algorithms which, based on the dead reckoning and inter-agent ranging, provides estimates of the agent positions, initialization algorithms for the estimation, and a user interface which exploits voice radio communication and 3D-audio to let the agents hear where they have each other.

    The second group of articles concerns low-level processing for extraction of spatial information of camera images (video), a prevailing infrastructure-free data source for relating an agent's position to the environment. These articles are focused on formalization and fast implementations of fundamental processing steps. An implementation of scale-space only relying on integer signal representation of image data and simple arithmetic operations is presented. Further, a unifying theory of feature point orientation assignment is derived and a novel method for the same is presented. Thereafter, the small but frequently occuring processing step in which image gradient samples are binned based on their argument, is treated and three fast solutions with varying properties are suggested. Finally, a localization system based on inertial navigation aided by imagery data is presented.

  • 11.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    De Angelis, Alessio
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Carbone, Paolo
    Department of Electronic and Information Engineering, University of Perugia.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    SIGNAL PROCESSING ISSUES IN INDOOR POSITIONING BY ULTRA WIDE BAND RADIO AIDED INERTIAL NAVIGATION2009In: Proc. EUSIPCO2009, EURASIP , 2009, 2161-2165 p.Conference paper (Refereed)
    Abstract [en]

    The difficulties and possibilities connected to indoor positioning suggest using several sources of navigational information. Apart from the signal processing of the individual sources this gives rise to the need for information fusion. This article aims at presenting and describing the signal processing methods and issues faced when constructing a navigation system based on a local ultra wide band (UWB) ranging system and an inertial navigation system (INS). The signal processing methods within the individual systems are described together with techniques for fusing the information from them. Finally, filtering results of experimental data is presented with expected convergence properties and positioning accuracy of below ±4 cm.

  • 12.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Gradient sample argument weighting for robust image region description2013In: Proceedings of the 2013 IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), IEEE conference proceedings, 2013, 1-4 p.Conference paper (Refereed)
    Abstract [en]

    The weighting of gradient sample arguments for the creation of descriptors of image regions is studied. The descriptors are interpreted as binned and weighted argument kernel density estimates and thereby their defining attributes are identified as the binning rules and the weighting. The weighting is further studied and four different weighting strategies are analyzed. The naive constant weighting is argued to have a poor robustness to image perturbations. As an answer to this, the customary gradient magnitude weighting is motivated. However, the short-comings of this approach are pointed out and two novel weighting strategies are suggested. The first suggested weighting gives a system parameter determining a distinctiveness to robustness trade-off with the customary magnitude weighting being a special case of it. The second suggested weighting gives a similar robustness as the first one, but at a lower computational cost. Finally, the effects of the different weighting strategies are demonstrated with real imagery data and synthetic perturbations.

  • 13.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Recursive Bayesian Initialization of Localization Based on Ranging and Dead Reckoning2013In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, IEEE conference proceedings, 2013, 1399-1404 p.Conference paper (Refereed)
    Abstract [en]

    The initialization of the state estimation in a localization scenario based on ranging and dead reckoning is studied. Specifically, we treat a cooperative localization setup and consider the problem of recursively arriving at a unimodal state estimate with sufficiently low covariance such that covariance based filters can be used to estimate an agent's state subsequently. The initialization of the position of an anchor node will be a special case of this. A number of simplifications/assumptions are made such that the estimation problem can be seen as that of estimating the initial agent state given a deterministic surrounding and dead reckoning. This problem is solved by means of a particle filter and it is described how continual states and covariance estimates are derived from the solution. Finally, simulations are used to illustrate the characteristics of the method and experimental data are briefly presented.

  • 14.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Robust recursive network clock synchronization2014In: 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), IEEE Computer Society, 2014, 6740335- p.Conference paper (Refereed)
    Abstract [en]

    A simple and statistically robust method for passive clock synchronization in sensor networks is presented. The method is not limited to passive (one-way communication) synchronization, but this scenario justifies the method. The recursive nature of the method and the targeted passive setup mean that it adds a minimum of requirements on the system in which it is used. Statistical characteristics of the method are quantified and real measurements are used to illustrate the robustness and performance gain relative to a naive Kalman filter based clock synchronization. Finally, C++ code that implements the suggested clock synchronization method, is provided in this article.

  • 15.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Time Synchronization and Temporal Ordering of Asynchronous Sensor Measurements of a Multi-sensor Navigation System2010In: 2010 IEEE-ION POSITION LOCATION AND NAVIGATION SYMPOSIUM PLANS, New York: IEEE conference proceedings, 2010, 241-246 p.Conference paper (Refereed)
    Abstract [en]

    In this article we propose a filter based method to solve the time synchronization and minimum delay temporal ordering problem of asynchronous sensor measurements. A problem which inevitably arise in the sensor fusion of a multi-sensor navigation system implemented in realtime on a general purpose operation system (OS) without using functionality dedicated to realtime applications. The time synchronization is done up to a constant error by linear filtering of time stamps given to each measurement. The filtered time stamps together with predicted future time stamps are then used in a measurement temporal ordering algorithm to achieve a minimal delay temporal ordering subject to a user specified jitter tolerance. Finally, experimental time synchronization and temporal ordering results from the system implemented with a typical set of navigation sensors are presented.

  • 16.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Kristensen, Johan
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A unifying approach to feature point orientation assignmentManuscript (preprint) (Other academic)
    Abstract [en]

    A general structure of an orientation measure for orientation assignment of 2D image feature points is heuristically motivated. The measure is discretized and general approximation methods are presented. Orientation assignment methods found in the literature are shown to exploit special cases of the general measure, which thereby provides a unifying framework for them. An analytical robustness analysis is conducted, giving a number of desirable robustness properties of the measure components. Following this, a detailed treatment of implementation issues such as gradient sampling and binning is given and based on the desirable properties and other implementation considerations, specific measure components with implementations are suggested. Together, this constitutes a novel feature point orientation assignment method, which we have called RAID. We argue that this method is considerably less expensive than comparable methods in the literature, and by means of a quantitative perturbation analysis, a significantly improved orientation assignment repeatability is demonstrated compared with the available methods found in the literature.

     

  • 17.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Kristensen, Johan
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fast scale-space approximation by cascaded box filters and integer signal representationManuscript (preprint) (Other academic)
    Abstract [en]

    A method for computationally inexpensive approximation of a set of scale levels in a Gaussian scale-space is presented. Box filters of different widths and orientations are cascaded to approximate the Gaussian kernels. The signal is downsampled at higher scales to reduce the number of samples and thereby the computational cost. Integer signal representation is used throughout the filtering, and the signal is downshifted as required to keep within the numerical range of the representation. The filtering require only add (and subtract) and shift operations to implement. An optimization problem is formulated for designing the filter cascade and a branch-and-bound technique is used to solve it. The level of approximation versus the computational cost is studied and based on a qualitative comparison with state-of-the-art approximation methods, it is concluded that the presented method shows unprecedented low computational cost and unique properties for low cost Gaussian scale-space approximation.

     

  • 18.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rantakokko, Jouni
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ohlsson, Martin
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Hari, K.V.S.
    Indian Institute of Science (IISc).
    Accurate Indoor Positioning of Firefighters using Dual Foot-mounted Inertial Sensors and Inter-agent Ranging2014In: Proceedings of the Position, Location and Navigation Symposium (PLANS), 2014 IEEE/ION, 2014Conference paper (Refereed)
    Abstract [en]

    A real-time cooperative localization system,utilizing dual foot-mounted low-cost inertial sensors and RFbasedinter-agent ranging, has been developed. Scenario-basedtests have been performed, using fully-equipped firefightersmimicking a search operation in a partly smoke-filledenvironment, to evaluate the performance of the TOR (TacticallOcatoR) system. The performed tests included realisticfirefighter movements and inter-agent distances, factors that arecrucial in order to provide realistic evaluations of the expectedperformance in real-world operations. The tests indicate that theTOR system may be able to provide a position accuracy ofapproximately two to three meters during realistic firefighteroperations, with only two smoke diving firefighters and onesupervising firefighter within range.

  • 19.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Schüldt, Christian
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Limes Audio, Sweden .
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Voice radio communication, pedestrian localization, and the tactical use of 3D audio2013In: 2013 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2013, IEEE Computer Society, 2013, 6817918- p.Conference paper (Refereed)
    Abstract [en]

    The relation between voice radio communication and pedestrian localization is studied. 3D audio is identified as a linking technology which brings strong mutual benefits. Voice communication rendered with 3D audio provides a potential low secondary task interference user interface to the localization information. Vice versa, location information in the 3D audio provides spatial cues in the voice communication, improving speech intelligibility. An experimental setup with voice radio communication, cooperative pedestrian localization, and 3D audio is presented and we discuss high level tactical possibilities that the 3D audio brings. Finally, results of an initial experiment, demonstrating the effectiveness of the setup, are presented.

  • 20.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Inertial Sensor Arrays - A Literature Review2016In: 2016 EUROPEAN NAVIGATION CONFERENCE (ENC), IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    Inertial sensor arrays present the possibility of improved and extended sensing capabilities as compared to customary inertial sensor setups. Inertial sensor arrays have been studied since the 1960s and have recently received a renewed interest, mainly thanks to the ubiquitous micro-electromechanical (MEMS) inertial sensors. However, the number of variants and features of inertial sensor arrays and their disparate applications makes the literature spread out. Therefore, in this paper we provide a brief summary and literature review on the topic of inertial sensor arrays. Publications are categorized and presented in a structured way; references to +300 publications are provide. Finally, an outlook on the main research challenges and opportunities related to inertial sensor arrays is given.

  • 21.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    De Angelis, Alessio
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Aquilanti, Claudia
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Gear scale estimation for synthetic speed pulse generation2011In: 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE conference proceedings, 2011, 1825-1828 p.Conference paper (Refereed)
    Abstract [en]

    In a motorized vehicle a number of easily measurable signals with frequency components related to the rotational speed of the engine can be found, e.g., vibrations, electrical system voltage level, and ambient sound. These signals could potentially be used to estimate the speed and related states of the vehicle. Unfortunately, such estimates would typically require the relations (scale factors) between the frequency components and the speed for different gears to be known. Consequently, in this article we look at the problem of estimating these gear scale factors from training data consisting only of speed measurements and measurements of the signal in question. The estimation problem is formulated as a maximum likelihood estimation problem and heuristics is used to find initial values for a numerical evaluation of the estimator. Finally, a measurement campaign is conducted and the functionality of the estimation method is verified on real data.

  • 22.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    A note on the limitations of ZUPTs and the implications on sensor error modeling2012In: Proceeding of 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 13-15th November 2012, 2012Conference paper (Refereed)
    Abstract [en]

    The limitations of zero-velocity-updates (ZUPTs) for aiding a foot-mounted inertial navigation system (INS) are studied. Multiple significant modeling errors related to the ZUPTs are pointed out and quantified. Their implications for the possibility to estimate systematic inertial sensor errors are discussed and it is argued that modeling and estimating such errors, in foot-mounted ZUPT-aided INSs, should be avoided in many cases.

  • 23.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Aligning the Forces-Eliminating the Misalignments in IMU Arrays2014In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, Vol. 63, no 10, 2498-2500 p.Article in journal (Refereed)
    Abstract [en]

    Ultralow-cost single-chip inertial measurement units (IMUs) combined into IMU arrays are opening up new possibilities for inertial sensing. However, to make these systems practical for researchers, a simple calibration procedure that aligns the sensitivity axes of the sensors in the array is needed. In this paper, we suggest a novel mechanical-rotation-rig-free calibration procedure based on blind system identification and a Platonic solid printable using a contemporary 3-D printer. The IMU array is placed inside the Platonic solid, and static measurements are taken with the solid subsequently placed on all sides. The recorded data are then used together with a maximum-likelihood-based approach to estimate the interIMU misalignment and the gain, bias, and sensitivity axis nonorthogonality of the accelerometers. The effectiveness of the method is demonstrated with calibration results from an in-house developed IMU array. MATLAB scripts for the parameter estimation and production files for the calibration device (solid) are provided.

  • 24.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    JOINT STATE AND MEASUREMENT TIME-DELAY ESTIMATION OF NONLINEARSTATE SPACE SYSTEMS2010In: Proc. ISSPA 2010, IEEE , 2010, 324-328 p.Conference paper (Refereed)
    Abstract [en]

    Sensor fusion algorithms often assume perfect time synchronization of the sensor clocks. In a practical sensor-actuator setup this is often difficult to achieve which in turn can give rise to systematic errors in the sensor fusion. In this article we suggest how the effect of the synchronization error from an unknown static or slowly varying measurement time-delays in a nonlinear state space system can be handled by linearizing the measurement equation in time. Based on the linearization an augmented system is constructed from which the system states and the delays can be jointly estimated. Expressions for the system, measurement, and covariance matrices of the augmented system are derived. Finally, the feasibility of the suggested approach is demonstrated by an example and a Monte-Carlo simulation.

  • 25.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Performance characterisation of foot-mountedZUPT-aided INSs and other related systems2010In: Proc. IPIN2010, IEEE , 2010, 1-7 p.Conference paper (Refereed)
    Abstract [en]

    Foot-mounted zero-velocity-update (ZUPT) aided inertial navigation system (INS) is a conceptually well known with publications in the area typically focusing on improved methods for filtering and addition of sensors and heuristics. Despite this, the performance characteristics, which would ultimately justify and give guidelines for such system modifications of ZUPT-aided INSs and other related systems, are in some aspects poorly documented. Unfortunately, the systems are non-linear, meaning that the performance is dependent on the system set-up, parameter setting, and the true trajectory. This complicates the process of evaluating performance and partially explains the few publications with detailed performance characterisation results. Therefore in this article we suggest and motivate methodologies for evaluating performance of ZUPT-aided INS and other related systems, we apply them to a suggested baseline set-up of the system, and study some aspects of the performance characteristics.

  • 26.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Hari, K.V.S.
    Department of ECE, Indian Institute of Science (IISc).
    Foot-mounted INS for Everybody: An Open-source Embedded Implementation2012In: 2012 IEEE/ION Position Location and Navigation Symposium (PLANS), IEEE , 2012, 140-145 p.Conference paper (Refereed)
    Abstract [en]

    We present an open-source, realtime, embedded implementation of a foot-mounted, zero-velocity-update-aided inertial navigation system. The implementation includes both hardware design and software, uses off-the-shelf components and assembly methods, and features a standard USB interface. The software is written in C and can easily be modified to run user implemented a1gorithlUS. The hardware design and the software are released under permissive open-source licenses and production files, source code, documentation, and further resources areavailable at www.openshoe.org. The reproduction cost for a single unit is below $800, with the inertial measurement unit makingup the bulk ($700). The form factor of the implementation is small enough for it to be integrated in the sole of a shoe. A performance evaluation of the system shows a position errors for short trajectories «100 [m)) of ± 0.2-1 % of the traveled distance, depending on the shape of trajectory.

  • 27.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zachariah, Dave
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jansson, Magnus
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Realtime Implementation of Visual-aided Inertial Navigation Using Epipolar Constraints2012In: 2012 IEEE/ION Position Location and Navigation Symposium (PLANS), IEEE , 2012, 711-718 p.Conference paper (Refereed)
    Abstract [en]

    A real-time implementation and the related theory of a visual-aided inertial navigation system are presented. The entire system runs on a standard laptop with off-the-shelf sensory equipment connected via standard interfaces. The visual-aiding is based on epipolar constraints derived from a finite visual memory. The navigational states are estimated with a squareroot sigma-point Kalman filter. An adaptive visual memory based on  statistical coupling is presented and used to store and discard images selectively. Timing and temporal ordering of sensory data are estimated recursively. The computational cost and complexity of the system is described, and the implementation is discussed in terms of code structure, external libraries, and important parameters. Finally, limited performance evaluation results of the system are presented.

  • 28.
    Nilsson, John-Olof
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zachariah, Dave
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skoog, Isaac
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging2013In: EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, E-ISSN 1687-6180, Vol. 164Article in journal (Refereed)
    Abstract [en]

    The implementation challenges of cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging are discussed and work on the subject is reviewed. System architecture and sensor fusion are identified as key challenges. A partially decentralized system architecture based on step-wise inertial navigation and step-wise dead reckoning is presented. This architecture is argued to reduce the computational cost and required communication bandwidth by around two orders of magnitude while only giving negligible information loss in comparison with a naive centralized implementation. This makes a joint global state estimation feasible for up to a platoon-sized group of agents. Furthermore, robust and low-cost sensor fusion for the considered setup, based on state space transformation and marginalization, is presented. The transformation and marginalization are used to give the necessary flexibility for presented sampling based updates for the inter-agent ranging and ranging free fusion of the two feet of an individual agent. Finally, characteristics of the suggested implementation are demonstrated with simulations and a real-time system implementation.

  • 29. Pasku, Valter
    et al.
    De Angelis, Alessio
    Moschitta, Antonio
    Carbone, Paolo
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Dwivedi, Satyam
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    A Magnetic Ranging Aided Dead-Reckoning Indoor Positioning System for Pedestrian Applications2016In: 2016 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE PROCEEDINGS, IEEE conference proceedings, 2016, 1526-1531 p.Conference paper (Refereed)
    Abstract [en]

    This paper investigates the applicability of a developed magnetic ranging and positioning system (MPS) as a support for a dead reckoning inertial navigation system for pedestrian applications. The integrated system combines the complementary properties of the separate systems, operating over long periods of time and in cluttered indoor areas with partial non-line-of-sight conditions. The obtained results show that the proposed approach can effectively improve the coverage area of the MPS and the operation time with bounded errors of the dead reckoning based system.

  • 30. Pasku, Valter
    et al.
    De Angelis, Alessio
    Moschitta, Antonio
    Carbone, Paolo
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Dwivedi, Satyam
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    A Magnetic Ranging-Aided Dead-Reckoning Positioning System for Pedestrian Applications2017In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 66, no 5, 953-963 p.Article in journal (Refereed)
    Abstract [en]

    This paper investigates the applicability of a developed Magnetic Positioning System (MPS) as a support for a dead-reckoning inertial navigation system (DR-INS) for pedestrian applications. The integrated system combines the complementary properties of the separate systems, operating over long periods of time and in cluttered indoor areas with partial nonline-of-sight conditions. The obtained results show that the proposed approach can effectively improve the coverage area of the MPS and the operation time with bounded errors of the DR-INS. In particular, a solution that provides bounded position errors of 1-2 m over significantly long periods of time up to 45 min, in realistic indoor environments, is demonstrated. Moreover, system applicability is also shown in those scenarios where arbitrary orientations of the MPS mobile node are considered and an MPS position estimate is not available due to less than three distance measurements.

  • 31. Rantakokko, J.
    et al.
    Nygards, J.
    Strömbäck, P.
    Andersson, P.
    Nilsson, John Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Integration of GNSS-receivers with dual foot-mounted INS in urban and indoor environments2016In: Proceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, 589-598 p.Conference paper (Refereed)
    Abstract [en]

    In safety-critical applications, including firefighter and law enforcement operations, infrastructure-free localization systems are typically required. These systems must provide accurate localization in all scenarios. Seamless indoor and outdoor localization and navigation, including in dense urban environments, are needed. Multi-sensor fusion algorithms constitute an integral part in all state-of-the-art indoor positioning systems. GNSS-receivers typically provide poor estimates of their own position uncertainty in dense urban and indoor environments, where significant position errors can be expected, which makes the design of a robust sensor fusion algorithm a challenge. Sensor fusion strategies for integration of a GNSS-receiver with foot-mounted inertial navigation systems (INS) are described and evaluated in this work. For a loosely coupled integration strategy, we suggest to use a cut-off criteria that governs when to discard the GNSS-positions and demonstrate that it can improve the position and heading accuracy in outdoor/indoor transition regions. Similarly, for a tightly coupled integration strategy, we suggest an approach with heavy-tailed measurement noise and demonstrate its capability to suppress inconsistent data and improve performance in the same regions.

  • 32.
    Rantakokko, Jouni
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Emilsson, Erika
    Swedish Defence Research Agency (FOI),.
    Rydell, Joakim
    Swedish Defence Research Agency (FOI),.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Localization and mapping technologies: an analysis of firefighter user needs and desired system functionalities2013Conference paper (Other academic)
  • 33.
    Simón Colomar, David
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Smoothing for ZUPT-aided INSs2012In: 2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings, IEEE conference proceedings, 2012, 6418869- p.Conference paper (Refereed)
    Abstract [en]

    Due to the recursive and integrative nature of zero-velocity-update-aided (ZUPT-aided) inertial navigation systems (INSs), the error covariance increases throughout each ZUPT-less period followed by a drastic decrease and large state estimate corrections as soon as ZUPTs are applied. For dead-reckoning with foot-mounted inertial sensors, this gives undesirable discontinuities in the estimated trajectory at the end of each step. However, for many applications, some degree of lag can be tolerated and the information provided by the ZUPTs at the end of a step can be made available throughout the step, eliminating the discontinuities. For this purpose, we propose a smoothing algorithm for ZUPT-aided INSs. For near real-time applications, smoothing is applied to the data in a step-wise manner requiring a suggested varying-lag segmentation rule. For complete off-line processing, full data set smoothing is examined. Finally, the consequences and impact of smoothing are analyzed and quantified based on real-data.

  • 34.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rantakokko, Jouni
    Zero-Velocity Detection-An Algorithm Evaluation2010In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 57, no 11, 2657-2666 p.Article in journal (Refereed)
    Abstract [en]

    In this paper, we investigate the problem of detecting-time epochs when zero-velocity updates can be applied in a foot-mounted inertial navigation (motion-tracking) system. We examine three commonly used detectors: the acceleration-moving variance detector, the acceleration-magnitude detector, and the angular rate energy detector. We demonstrate that all detectors can be derived within the same general likelihood ratio test (LRT) framework, given the different prior knowledge about the sensor signals. Further, by combining all prior knowledge, we derive a new LRT detector. Subsequently, we develop a methodology to evaluate the performance of the detectors. Employing the developed methodology, we evaluate the performance of the detectors using leveled ground, slow (approximately 3 km/h) and normal (approximately 5 km/h) gait data. The test results are presented in terms of detection versus false-alarm probability. Our preliminary results show that the new detector performs marginally better than the angular rate energy detector that outperforms both the acceleration-moving variance detector and the acceleration-magnitude detector.

  • 35.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    An open-source multi inertial measurement unit (MIMU) platform2014In: 1st IEEE International Symposium on Inertial Sensors and Systems, ISISS 2014 - Proceedings, IEEE Computer Society, 2014Conference paper (Refereed)
    Abstract [en]

    An open-source low-cost multi inertial measurement unit (MIMU) systems platform is presented. First, the layout and system architecture of the platform, as well as the novel communication interface used to simultaneously communicate with the 18 IMUs in the platform are described. Thereafter, the potential gains of using a MIMU system are described and discussed. Finally, the error characteristics of the platform, when stationary, are illustrated using Allan variance plots.

  • 36.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Handel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Nehorai, Arye
    Inertial Sensor Arrays, Maximum Likelihood, and Cramer-Rao Bound2016In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 64, no 16, 4218-4227 p.Article in journal (Refereed)
  • 37.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Evaluation of zero-velocity detectors for foot-mounted inertial navigation systems2010In: 2010 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2010, 2010Conference paper (Refereed)
    Abstract [en]

    A study of the performance of four zero-velocity detectors for a foot-mounted inertial sensor based pedestrian navigation system is presented. The four detectors are the acceleration moving variance detector, the acceleration magnitude detector, the angular rate energy detector, and a novel generalized likelihood ratio test detector, refereed to as the SHOE. The performance of each detector is assessed by the accuracy of the position solution provided by the navigation system employing the detector to perform zero-velocity updates. The results show that for leveled ground forward gait at a speed of 5 km/h, the angular rate energy detector and the SHOE give the highest performance, with a position accuracy of 0.14% of the travelled distance. The results also indicate that during leveled ground forward gait, the gyroscope signals hold the most reliable information for zerovelocity detection.

  • 38.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Pedestrian tracking using an IMU array2014In: 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), IEEE Computer Society, 2014, 6740346- p.Conference paper (Refereed)
    Abstract [en]

    Ubiquitous and accurate tracking of pedestrians are an enabler for a large range of emerging and envisioned services and capabilites. To track pedestrians in prevailing indoor environments, inertial measurement units (IMUs) may be used to implement foot-mounted inertial navigation. Today emerging ultra-low-cost IMUs are taking a leading role in the advancement of the IMU performance-to-cost boundary. Unfortunately, the performance of these IMUs are still insufficient to allow extended stand-alone tracking. However, the size, price, and power consumption of single-chip ultra-low-cost IMUs makes it possible to combine multiple IMUs on a single PCB, creating an IMU array. The feasibility of such hardware has recently been demonstrated. On the other hand, the actual gain of using such multi-IMU systems in the pedestrian tracking application is unclear. Therefore, based on an in-house developed IMU array, in the article we demonstrate that foot-mounted inertial navigation with an IMU array is indeed possible and benefitial. The error characteristics of the setup and different ways of combining the inertial measurements are studied and directions for further research are given.

  • 39.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Nehorai, Arye
    Arrays of single-chip IMUs2015In: Proc. International Conference on Indoor Positioning and Indoor Navigation (IPIN), Calgary, Canada: University of Calgary , 2015Conference paper (Refereed)
    Abstract [en]

    The development of ultralow-cost single-chip IMUs nowmake it feasible to construct massive IMU arrays. Such arrays giveproperties not attainable by single IMUs. Specifically, non-colocatedaccelerometers provide rotational information with complementary char-acteristics to that provided by the gyroscopes. In this poster we reviewthe signal model of multi-IMU systems and present experimental resultsfrom an in-house developed IMU array.

  • 40.
    Skog, Isaac
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zachariah, Dave
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fusing the information from two navigation systems using an upper bound on their maximum spatial separation2012In: 2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings, IEEE , 2012, 6418862- p.Conference paper (Refereed)
    Abstract [en]

    A method is proposed to fuse the information from two navigation systems whose relative position is unknown, but where there exists an upper limit on how far apart the two systems can be. The proposed information fusion method is applied to a scenario in which a pedestrian is equipped with two foot-mounted zero-velocity-aided inertial navigation systems; one system on each foot. The performance of the method is studied using experimental data. The results show that the method has the capability to significantly improve the navigation performance when compared to using two uncoupled foot-mounted systems.

1 - 40 of 40
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