Track-before-detect procedures for detection of extended object
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RESEARCH
Open Access
Track-before-detect procedures for detection of extended object Ling Fan*, Xiaoling Zhang and Jun Shi
Abstract In this article, we present a particle filter (PF)-based track-before-detect (PF TBD) procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/ absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance). Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects. Keywords: extended targets, track-before-detect, particle filter, signal-to-noise ratio
Introduction Most target tracking algorithms assume a single point positional measurement corresponding to a target at each scan. However, high resolution sensors are able to supply the measurements of target extent in one or more dimensions. For example, a high-resolution radar provides a useful measure of down-range extent given a reasonable signal-to-noise ratio (SNR). The possibility to additionally make use of the high-resolution measurements is referred as extended object tracking [1]. Estimation of the object shape parameters is especially important for track maintenance [2] and for the object type classification. More recent approaches to tracking extended targets have been investigated by assuming that the measurements of target extent are available [1-5]. However, the measurements of extended targets provided by the high resolution sensor are inaccurate in a low SNR environment since those are obtained by threshold-based decisions made on the raw measurement at each scan. Ristic et al. [3] investigated the influence of extent measurement accuracy on the estimation accuracy of target shape parameters, and demonstrated that the estimation of target shape parameters is unbelievable when the measurement of extended targets is not available. An alternative approach, referred as track-before-detect * Correspondence: [email protected] School of Electronic Engineering, University of Electronic Science and Technology of China, Cheng du, China
(TBD), consists of using raw, unthresholded sensor data. TBD-based procedures jointly process several consecutive scans and, relying on a target kinematics, jointly declare the presence of a target and, eventually, its track, and show superior detection performance over the conventional methods. In previously developed TBD algorithms, the target is assumed to be a point target [6-18]. Recently extension of TBD method for tracking extended targets has been considered in [19], by modeling the target extent as a spatial probability distribution. In this study, an ellipsoidal model of target shape proposed in [1-3] is adopted. The elliptical model is convenient as down-range and cross-range extent vary smoothly with orientation relative to the line-of-sight (LOS) between the observer and the target. Th
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