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The Histogram PMHT is a parametric track-before-detect method that has good detection performance and low computation complexity. However, the method assumes a known clutter distribution. This paper introduces a method for learning a non-uniform clutter map where the map is represented as a mixture of parameterised components. The modified Histogram PMHT is compared with the uniform clutter model...
In this paper we investigate a multi-hypothesis algorithm for tracking multiple underwater targets in the three dimensional (3D) space using two acoustic sensor arrays attached to the same underwater platform. One of the arrays measures the bearing to the target and the other array, consisting of three spatially distributed hydrophones, measures two time difference of arrivals of the acoustic wave...
In this paper we consider the problem of multitarget tracking using range and range-rate measurements collected from a single maneuvering platform. Although bearings-only tracking has been studied extensively, only a few studies exist in the literature that consider range-only tracking. The motivating application for this work is maritime surveillance using radars equipped with inverse synthetic aperture...
A relationship between differential geometry and estimation theory was lacking until the work of Bates and Watts in the context of nonlinear parameter estimation. They used differential geometry based curvature measures of nonlinearity (CMoN), namely, the parameter-effects and intrinsic curvatures to quantify the degree of nonlinearity of a general multi-dimensional nonlinear parameter estimation...
The problem is joint detection and tracking of possibly several objects moving through a region of interest. A wireless sensor network (WSN), deployed in the region, collects the acoustic energy measurements and sends them to the fusion center for processing. The problem is cast in the sequential Bayesian estimation framework and solved using a particle filter. The number of objects is unknown and...
The problem of single-sensor bearings-only tracking continues to present challenges to tracking algorithms, particularly in certain difficult scenarios such as ones with high bearing rates. In such scenarios, the performance of the recently introduced shifted Rayleigh filter (SRF) is compared with that of other techniques such as extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle...
In multi-sensor multi-target bearings-only tracking we often see false intersections of bearings known as ghosts. When the bearing measurements from each sensor have been associated to form sequences termed threads, the problem is to associate pairs of threads to identify the true target intersections. In this paper we present two algorithms: (i) classical bayesian thread association (CBTA) and (ii)...
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