Robust Association Algorithm for Multiple Radar Maritime Targets Based on Trusted Association Pairs

Abstract

The invention belongs to the technical field of marine radar information fusion and provides a real-time track robust association technology suitable for a target on the sea surface under the condition that a system error exists, namely a multi-radar marine target robust association algorithm based on a credible association pair. According to the characteristics of target tracks of ships on the sea surface, under the condition that it is confirmed that the system error exists, a pair of tracks which come from different sensors and originate from the same target is defined as the credible track association pair, wherein the tracks are close to each other on the sea surface, and no other track exists within a certain range nearby the tracks. According to the multi-radar marine target robust association algorithm, the credible track association pair on the sea surface is extracted based on the unit average constant false alarm detection method, the credible track association pair is used for obtaining track deviation caused by the system error, and association of the tracks with the same source is realized based on the classic track association algorithm after error compensation is conducted on original radar data. Compared with the traditional multi-sensor track robust association algorithm, the multi-radar marine target robust association algorithm mainly has the advantages that the computing process is simple and convenient, computing time is short, and the requirement for the real-time performance of a radar tracking fusion system can be met.

Description

[0001] 1. Technical field [0002] The invention belongs to the technical field of sea radar information fusion, and provides a real-time track anti-difference correlation algorithm for sea surface targets under the condition that system errors exist. [0003] 2. Background technology [0004] In the multi-target multi-sensor tracking fusion system, in order to eliminate the repeated tracking of the same target by different sensors and effectively improve the tracking accuracy of track data, it is necessary to perform track correlation on the target measurement data reported by multiple sensors. Due to the influence of factors such as target distribution, target motion and data processing methods, it is often difficult for the fusion center to accurately correlate the tracks of each target, and the existence of sensor system errors further increases the complexity of track correlation processing. [0005] The traditional track correlation algorithm ignores the existence of syst...

AI Technical Summary

Problems solved by technology

Due to the influence of factors such as target distribution, target motion law, and data processing methods, it is often difficult for the fusion center to accurately correlate the tracks of each target, and the existence of sensor system errors further increases the complexity of track correlation processing.

[0005] The traditional track correlation algorithm ignores the existence of systematic errors, assumes that the state estimation data of the target only contains random errors, and treats the track correlation as a global optimization problem, which causes a large false correlation rate and missing correlation in practical applications. Rate

Existing multi-sensor track robust correlation techniques such as track robust correlation algorithms based on target topology information or image registration technology have a substantial theoretical basis, but the calculation process is complex and the calculation time is long, which is difficult to meet the requirements of the target tracking fusion system. real-time requirements, the real-time track robustness correlation technology suitable for multi-radar sea targets needs to be solved urgently

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