PROJECT TITLE:

Reference pattern-based track-to-track association with biased data

ABSTRACT:

A heuristic track-to-track association algorithm for sensors with azimuth biases and vary biases is proposed based mostly on a reference pattern (REP) of the target. For a given target, the structure revealed by its neighboring targets is named as its REP. To catch up on the relative azimuth bias between sensors, we tend to modify the optimal subpattern assignment metric, which makes the derived association price matrix insensitive to sensor biases. Simulation results demonstrate the superior performance of the proposed algorithm.


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