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In this paper a Probability Hypothesis Density (PHD) filter based track-before-detect (TBD) algorithm is proposed for Multiple-Input-Multiple-Output (MIMO) radars. The PHD filter, which propagates only the first-order statistical moment of the full target posterior, is a computationally efficient solution to multitarget tracking problems with varying number of targets. The proposed algorithm avoids...
A standard assumption in most tracking algorithms, like the Probabilistic Data Association (PDA) filter, Multiple Hypothesis Tracker (MHT) or the Multiframe Assignment Tracker (MFA), is that a target is detected at most once in a frame of data used for association. This one-to-one assumption is essential for correct measurement-to-track associations. When this assumption is violated, the above algorithms...
Recent advances in Multiple-Input-Multiple-Output (MIMO) radar systems show that they have the potential to improve detection and localization performance of targets over bistatic and multistatic radars. Unlike beam forming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO system exploits the independence between signals at the array elements due...
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