Indoor target tracking using high doppler resolution passive Wi-Fi radar

Chen, Qing-Chao; Tan, Bo; Woodbridge, K.; Chetty, Kevin

doi:10.1109/icassp.2015.7179036

Cited by 23 publications

(14 citation statements)

References 17 publications

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“…Recently, extensive research [ Chen et al , ; Daout et al , ; Gogineni et al , ; Griffiths and Long , ; Howland et al , ; Stinco et al , ] has been conducted in passive radar systems that utilize illuminators of opportunity owing to their advantages of low implementation costs, low probability of intercept [ Shi et al , , ; Zhang et al , ], and so on. The two‐dimensional target localization problem is investigated for the WiFi‐based multistatic passive radar [ Falcone et al , ], and different target localization schemes are proposed based on different sets of available measurements.…”

Section: Introductionmentioning

confidence: 99%

Modified Cramér‐Rao lower bounds for joint position and velocity estimation of a Rician target in OFDM‐based passive radar networks

et al. 2017

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Owing to the increased deployment and the favorable range and Doppler resolutions, orthogonal frequency‐division multiplexing (OFDM)‐based L band digital aeronautical communication system type 1 (LDACS1) stations have become attractive systems for target surveillance in passive radar applications. This paper investigates the problem of joint parameter (position and velocity) estimation of a Rician target in OFDM‐based passive radar network systems with multichannel receivers placed on moving platforms, which are composed of multiple OFDM‐based LDACS1 transmitters of opportunity and multiple radar receivers. The modified Cramér‐Rao lower bounds (MCRLBs) on the Cartesian coordinates of target position and velocity are computed, where the received signal from the target is composed of dominant scatterer (DS) component and weak isotropic scatterers (WIS) component. Simulation results are provided to demonstrate that the target parameter estimation accuracy can be improved by exploiting the DS component. It also shows that the joint MCRLB is not only a function of the transmitted waveform parameters, target radar cross section, and signal‐to‐noise ratio but also a function of the relative geometry between the target and the passive radar networks. The analytical expressions of MCRLB can be utilized as a performance metric to access the target parameter estimation in OFDM‐based passive radar networks in that they enable the selection of optimal transmitter‐receiver pairs for target estimation.

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Section: Introductionmentioning

confidence: 99%

Modified Cramér‐Rao lower bounds for joint position and velocity estimation of a Rician target in OFDM‐based passive radar networks

et al. 2017

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“…Background and Motivation P ASSIVE radar network systems have recently received a growing interest, which use signals of opportunity such as television broadcasts [1], frequency modulation (FM) Manuscript M. Sellathurai is with the School of Engineering and Physical Sciences, Herriot Watt University, Edinburgh EH14 4AS, U.K. e-mail: mathini@ieee.org. commercial radio [2], global positioning system (GPS) [3], universal mobile telecommunications systems (UMTS) [4][5][6], and WiFi [7], as illuminators for target detection, estimation, and classification. Since only receivers are required in passive radar networks, they have the advantages of low probability of intercept (LPI) [8][9][10] and low implementation costs.…”

Section: Introductionmentioning

confidence: 99%

Transmitter Subset Selection in FM-Based Passive Radar Networks for Joint Target Parameter Estimation

et al. 2016

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Passive radar network systems utilize multiple transmitters of opportunity and multichannel receivers to offer remarkable performance improvement due to the advantage of signal and spatial diversities. The frequency modulation (FM) commercial radio signals have become attractive for passive radar applications owing to their wide-spread availability and the favourable Doppler resolution. In this paper, two transmitter subset selection schemes, balancing the trade-off between target parameter estimation accuracy and infrastructure utilization, are proposed for FM-based passive radar networks. In the first, the subset size of selected transmitters employed in the estimation process is minimized by effectively selecting a subset of transmitters such that the required target parameter estimation mean-square error (MSE) threshold is attained. In the second, an optimal subset of transmitters of a predetermined size κ is selected such that the estimation MSE is minimized. These problems are formulated as a knapsack problem (KP), where the coherent Cramér-Rao lower bound (CRLB) is used as a performance metric. Both transmitter subset selection schemes are tackled with greedy selection algorithms by successively selecting transmitters so as to minimize the performance gap between the CRLB and a predetermined MSE threshold or a predetermined subset size. Numerical simulations demonstrate that the problem of transmitter subset selection is not only a function of the transmitted waveforms but also of the relative geometry between the target and the passive radar network systems, which leads to reductions in both computational load and signal processing costs.

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“…Despite of its successful application in target classification, the micro‐Doppler signature has not been widely applied in human localisation and tracking, due to the low range resolution of such radar systems. A Doppler‐only method was reported for a single person tracking in the absence of accurate range information [14]. As the range resolution of the passive Wi‐Fi radar system is poor, human tracking is implemented directly by Kalman prediction using only Doppler measurements.…”

Section: Introductionmentioning

confidence: 99%

“…In multi‐target environments, it is difficult to determine which Doppler measurements correspond to which targets. Thus, the tracking framework in [14] may not be able to handle multi‐target tracking (MTT) scenarios.…”

Section: Introductionmentioning

confidence: 99%

Range–Doppler‐based centralised framework for human target tracking in multistatic radar

Zhang

Jin

et al. 2017

IET Radar, Sonar & Navigation

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Indoor target tracking using high doppler resolution passive Wi-Fi radar

Cited by 23 publications

References 17 publications

Modified Cramér‐Rao lower bounds for joint position and velocity estimation of a Rician target in OFDM‐based passive radar networks

Modified Cramér‐Rao lower bounds for joint position and velocity estimation of a Rician target in OFDM‐based passive radar networks

Transmitter Subset Selection in FM-Based Passive Radar Networks for Joint Target Parameter Estimation

Range–Doppler‐based centralised framework for human target tracking in multistatic radar

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