Overlapping Secondary Surveillance Radar Replies Separation Algorithm Based on MUSIC
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摘要: 为了提高在高密度信号环境下对二次监视雷达(SSR)应答信号的接收性能，该文提出一种将信源数估计和信号到达方向(DOA)估计相结合构建分离矩阵实现交叠信号分离的算法。首先根据交叠信号量测的特征值分布来确定交叠信号的个数；然后利用MUSIC算法作谱峰搜索得到各信号的DOA，并重构混合矩阵；最后通过计算混合矩阵的广义逆得到分离矩阵，并实现对交叠信号的分离。以6阵元均匀线阵为前提进行仿真分析，结果表明所提分离算法可达到90%以上的分离成功率，分离性能和独立成分分析(ICA)算法相当，优于基于投影技术分离算法(PA)，但计算量远小于ICA算法，不足ICA算法计算量1/10，更易于工程化应用。Abstract: In order to improve the reception performance of Secondary Surveillance Radar (SSR) replies in high-density signal environment, a separation algorithm is proposed, which constructs the separating matrix with estimating the source number and the Direction Of Arrival (DOA) of signal. Firstly, the number of overlapping signals is determined with the eigenvalues distribution of the measurements. Secondly, the mixing matrix with the DOA of signals, which is estimated by peak value searching in MUSIC algorithm. Finally, the separating matrix is estimated by calculating the Moore-Penrose inverse of the reconstructed mixing matrix, achieving separation of overlapping signals. Simulation is done based on uniform linear array with 6 elements. The results show that the proposed separation algorithm can achieve more than 90% success rate to separate two short Mode S replies, and the separating performance is similar to the Independent Component Analysis (ICA) algorithm and is better than Projection Algorithm (PA). The amount of calculation is less than 10 percent of ICA algorithm, thus the proposed separation algorithm is easier to engineering application.
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表 1 交叠信号个数检测正确概率(%)
DOA 4 dB 8 dB 12 dB 16 dB 20 dB 0° 93.63 95.84 97.51 98.61 99.17 15° 93.07 95.84 96.95 97.78 98.89 30° 92.80 95.29 96.40 97.23 98.61 45° 90.86 93.91 95.84 96.40 98.34 60° 85.87 91.97 95.29 95.29 98.06 75° 72.58 78.95 87.81 93.91 97.51 90° 71.75 77.84 82.55 86.70 90.03 
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