Multi-target tracking with PHD filter using Doppler-only measurements

Abstract

In this paper, we address the problem of multi-target detection and tracking over a network of separately located Doppler-shift measuring sensors. For this challenging problem, we propose to use the probability hypothesis density (PHD) filter and present two implementations of the PHD filter, namely the sequential Monte Carlo PHD (SMC-PHD) and the Gaussian mixture PHD (GM-PHD) filters. Performances of both filters are carefully studied and compared for the considered challenging tracking problem. Simulation results show that both PHD filter implementations, successfully tracks multiple targets using only Doppler shift measurements. Moreover, as a proof-of-concept, an experimental setup consisting of a network of microphones and a loudspeaker was prepared. Experimental study results reveal that it is possible to track multiple ground targets using acoustic Doppler shift measurements in a passive multi-static scenario. We observed that the GM-PHD is more effective, efficient and easy to implement than the SMC-PHD filter.

Multiperson Tracking With a Network of Ultrawideband Radar Sensors Based on Gaussian Mixture PHD Filters

“…In addition, to accommodate nonlinear dynamics and measurement models, several different nonlinear extensions of the GM-PHD are also proposed in the literature [40], [41]. These nonlinear extensions of the GM-PHD filter have successfully been used in many different applications, in which nonlinear target dynamics and measurement models are employed [42]- [48]. In this work, in order to accommodate nonlinear Gaussian models, an adaptation of the GM-PHD filter (called as EK-PHD) is employed based on the idea of extended Kalman filter (EKF), where the local linearization of the nonlinear measurement function h(x) (i.e., H k defined in (6)) is used [39].…”

Identification of Multi-gait Using Spectral Analysis of Gravity Center Track

“…M.B. Guldogan et al in [6] addressed the problem of multi-target detection and tracking over a network of separately located Doppler-shift measuring sensors. W. Li et al in [7] studied the problem of multi-target tracking with glint noise in the formulation of random finite set theory.…”

Group sparsity based multi-target tracking in multi-static passive radar systems using Doppler-only measurements

“…MTT refers to a problem of jointly estimating the number of targets and their states, at successive time intervals, from a noisy and cluttered set of observations [5]. In recent years, the problem of MTT using Doppler-only measurements has emerged as an area of interest, specially in the context of multi-static passive radar (MPR) systems (e.g., [6][7][8]), as the Doppler sensors have become increasingly accurate and inexpensive. A Doppler-only tracking passive radar system being considered comprises an illuminator of opportunity (e.g., DAB/DVB broadcast station, FM radio transmitter, and † The work of S. Subedi, Y. D. Zhang, and M. G. Amin was supported in part by a subcontract with Defense Engineering Corporation for research sponsored by the Air Force Research Laboratory under Contract FA8650-12-D-1376.…”