A Multi-Scan Joint Tracking and Classification Method for Weak Targets
Kai Zeng, Wei Yi, Qiyun Peng, Jie Deng · 2020
This paper proposes a novel multi-scan algorithm with the task of the joint tracking and classification (JTC) for weak targets to address the limitations existed in the traditional single-scan JTC algorithms based on the threshold detection. At each scan, the measurements both from the radar system and the electronic support measures (ESM) sensor, which is one of the passive and bearing-only sensors, are first adopted. Then, by using these measurements of multiple scans, a fast multi-scan JTC (MS-JTC) algorithm is proposed. It is shown that the MS-JTC can bring about a better signal to noise ratio (SNR) for radar systems and better classification due to the accumulation information of multiple scans. Finally, by comparing with the existing single-scan-based algorithm, simulation experiments are executed to validate the effectiveness of our proposed algorithm.