Simultaneous Target and Multipath Positioning

Li, Li; Krolik, Jeffrey L.

doi:10.1109/jstsp.2013.2289949

Cited by 33 publications

(21 citation statements)

References 53 publications

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“…In [20], the identifiability of the joint MD and multipath parameter estimation with both TOA and angle-of-arrival (AOA) measurements are analyzed by studying the Cramer-Rao lower bound (CRLB) for the estimated parameters. Ref.…”

Section: F Identifiabilitymentioning

confidence: 99%

“…In [17], a tracking scheme is proposed by modeling both LOS and reflections and using JPDAF to associate measurements with their corresponding path origins. In [20], a tracking and mapping algorithm is proposed that models LOS, reflections, and point scattering paths and uses MHTF to associate measurements with their path origins. The results of these methods are sensitive to DA uncertainty [22].…”

Section: Introductionmentioning

confidence: 99%

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TOA-Based Indoor Localization and Tracking With Inaccurate Floor Plan Map via MRMSC-PHD Filter

2019

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This paper proposes a novel indoor localization scheme to jointly track a mobile device (MD) and update an inaccurate floor plan map using the time-of-arrival measured at multiple reference devices (RDs). By modeling the floor plan map as a collection of map features, the map and MD position can be jointly estimated via a multi-RD single-cluster probability hypothesis density (MSC-PHD) filter. Conventional MSC-PHD filters assume that each map feature generates at most one measurement for each RD. If single reflections of the detected signal are considered as measurements generated by map features, then higher-order reflections, which also carry information on the MD and map features, must be treated as clutter. The proposed scheme incorporates multiple reflections by treating them as virtual single reflections reflected from inaccurate map features and traces them to the corresponding virtual RDs (VRDs), referred to as a multi-reflection-incorporating MSC-PHD (MRMSC-PHD) filter. The complexity of using multiple reflection paths arises from the inaccuracy of the VRD location due to inaccuracy in the map features. Numerical results show that these multiple reflection paths can be modeled statistically as a Gaussian distribution. A computationally tractable implementation combining a new greedy partitioning scheme and a particle-Gaussian mixture filter is presented. A novel mapping error metric is then proposed to evaluate the estimated map?s accuracy for plane surfaces. Simulation and experimental results show that our proposed MRMSC-PHD filter outperforms existing MSC-PHD filters by up to 95% in terms of average localization and by up to 90% in terms of mapping accuracy.

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Section: F Identifiabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

TOA-Based Indoor Localization and Tracking With Inaccurate Floor Plan Map via MRMSC-PHD Filter

2019

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“…For certain sensing systems, however, one target may result in multiple measurements that are not spatially structured due to multipath propagation phenomenon [4]. Such sensing systems, called multipath detection systems (MDS) in this paper, include skywave over-the-horizon radar (OTHR) [5], passive coherent location (PCL) system [6], the sensors work in urban environments [7], [8], etc. In OTHR, high-frequency radiowave propagation through a layered ionosphere often gives rise to multiple propagation paths, resulting in multiple resolved detections for one target at each radar scan.…”

Section: Introductionmentioning

confidence: 99%

Joint Target Detection and Tracking in Multipath Environment: A Variational Bayesian Approach

Lan¹,

Sun

Wang

et al. 2020

IEEE Trans. Aerosp. Electron. Syst.

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We consider multitarget detection and tracking problem for a class of multipath detection system where one target may generate multiple measurements via multiple propagation paths, and the association relationship among targets, measurements and propagation paths is unknown. In order to effectively utilize multipath measurements from one target to improve detection and tracking performance, a tracker has to handle high-dimensional estimation of latent variables including target active/dormant meta-state, target kinematic state, and multipath data association. Based on variational Bayesian inference, we propose a novel joint detection and tracking algorithm that incorporates multipath data association, target detection and target state estimation in a unified Bayesian framework. The posterior probabilities of these latent variables are derived in a closed-form iterative manner, which is effective for reducing the performance deterioration caused by the coupling between estimation errors and identification errors.Loopy belief propagation is exploited to approximately calculate the probability of multipath data association, saving the computational cost significantly. Simulation results of over-the-horizon radar multitarget tracking show that the proposed algorithm outperforms multihypothesis multipath track fusion and multi-detection (hypothesis-oriented) multiple hypothesis tracker, especially under low signalto-noise ratio circumstance.

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“…The basic multipath physics involved is relevant also to the see-behind-corner case. Multi-static sensor arrangements (MIMO) have been studied to improve on, e.g., target localization 20,21 .…”

Section: Introductionmentioning

confidence: 99%

Radar measurements of moving objects around corners in a realistic scene

et al. 2014

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In urban warfare or for surveillance purposes, having a stand-off radar system with the capability of "seeing" behind corners would be of great importance. The possibility of detecting moving people and objects in the shadow region of a street corner using diffraction and multipath propagation of radar waves has previously been demonstrated in experimental set-ups. Detections of movements in a realistic scene are investigated in this study.The measurements were made using a radar operating at X-band (9.95-10.05 GHz) in a stepped-frequency mode. In these experiments a semi-monostatic single receiver-transmitter radar system was used as a data collector. The moving objects in the measurements are persons walking, riding a bicycle and driving a car. All detections were made after Doppler filtering, using coherent subtraction between different frequency sweeps. An adaptive detection threshold has been applied and the detections can be shown in range vs. time plots, where the movement of the object can been seen as detection tracks.Detections of movements are made fairly easily. Target returns after one and two wall reflections before the target, i.e., in total five reflections between transmission and receiving, can be identified. No attempt to exploit diffraction was made in these measurements. The background is generally well suppressed by the signal processing. Simultaneous detection of two objects moving in the scene can be made, when allowed by the range resolution. The results are promising with low false alarm rates. Future work will address positioning and micro-Doppler analysis of the measurement data.

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Simultaneous Target and Multipath Positioning

Cited by 33 publications

References 53 publications

TOA-Based Indoor Localization and Tracking With Inaccurate Floor Plan Map via MRMSC-PHD Filter

TOA-Based Indoor Localization and Tracking With Inaccurate Floor Plan Map via MRMSC-PHD Filter

Joint Target Detection and Tracking in Multipath Environment: A Variational Bayesian Approach

Radar measurements of moving objects around corners in a realistic scene

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