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In this paper, a new array signal processing technique, which make use of the cross ambiguity function calculation, is proposed. Developed technique estimates direction of arrival (DOA), time delay, Doppler shift and amplitude corresponding to each impinging signal onto a sensor array in an iterative manner. Performances of the proposed technique cross(More)
In this paper, we explore the potential of networked microphone arrays for multiple target tracking. Tracking is accomplished by using the direction-of-arrival (DOA) estimates of multiple microphone arrays. Each microphone array obtains the DOA estimates by using the wideband extensions of the multiple signal classification (MUSIC) technique. Based on these(More)
Over the past decade, the human micro-Doppler signature has been a subject of intense research. In particular, much work has been done in relation to computing features for use in a variety of classification problems, such as arm swing detection, activity classification, and target identification. Although dozens of features have been proposed for these(More)
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(More)
In this paper, we present the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple ground targets using a passive acoustic-sensor network. For this purpose, an experimental setup consisting of a network of microphones and a loudspeaker was prepared. Non-cooperative transmissions from a loudspeaker (i.e.(More)
A new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delay–Doppler domain by using the cross-ambiguity function (CAF) for efficient exploitation of the delay–Doppler diversity of the multipath components. Clusters of multipath(More)
In this paper, we analyze the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple non-cooperative targets using Doppler-only measurements in a passive sensor network. Clutter, missed detections and multi-static Doppler variances are incorporated into a realistic multi-target scenario. Simulation results(More)
It is well-known that the motion of an acoustic source can be estimated from Doppler shift observations. It is however not obvious how to design a sensor network to efficiently deliver the localization service. In this work a rather simplistic motion model is proposed that is aimed at sensor networks with realistic numbers of sensor nodes. It is also(More)
In this letter, we study the problem of distributed detection and tracking of a target over a network of separately located Doppler-shift sensors. For this challenging problem, we propose consensus Gaussian mixture - Bernoulli (CGM-Ber) filter. The simulation results prove the robust and effective performance of the proposed approach in a challenging(More)
In this paper, a new array signal processing technique by using particle swarm optimization (PSO) is proposed to identify multipath channel parameters. The proposed technique provides estimates to the channel parameters by finding a global minimum of an optimization problem. Since the optimization problem is formulated in the cross-ambiguity function (CAF)(More)