Track-to-Track Association Technique in Radar Network in the Presence of Systematic Errors

Abstract

<p class="MsoNormal"> <span><span lang="EN-US">The presence of systematic measuring errors complicates track-to-track association, spatially separates the tracks that correspond to the same true target, and seriously decline the performances of traditional track-to-track association algorithms. Consequently, the influence of radar systematic errors on tracks from different radars, which is described as some rotation and translation, has been analyzed theoretically in this paper. In addition, a novel approach named alignment-correlation method is developed to estimate and reduce this effect, align and correlate tracks accurately without prior registration using phase correlation technique and statistic binary track correlation algorithm. Monte-Carlo simulation results illustrate that the proposed algorithm has good performance in solving the track-to-track association problem with systematic errors in radar network and could provide effective and reliable associated tracks for the next step of registration.</span></span> </p

Robust track-to-track association in the presence of sensor biases and missed detections

“…Step 2: Update the transformation parameter of f. When given the correspondence matrix Z, the optimal transformation parameterd andŵ in (17) can be obtained by minimizing the following function [19] ðd;ŵÞ ¼ arg min…”

“…In [16], a track-to-track association approach was presented based on the structural similarity, which is suitable for dealing with the case with small range biases. A two-stage algorithm [17] sequentially performs track alignment and track correlation. In [18], an analytic approach was given to predict the performance of track-to-track performance without using the costly Monte-Carlo simulation method.…”