DTMB外辐射源雷达纠错算法性能评估

Performance evaluation of decoding algorithms for DTMB-based passive radar

摘要:

低密度奇偶检验(LDPC)码纠错算法是地面数字多媒体广播(DTMB)外辐射源雷达参考信号重构的关键技术之一。LDPC码纠错算法可以改善噪声带来的数据误码，但是计算复杂度高。结合图形处理器(GPU)运算能力强的优点，本文提出了基于硬判决、混合判决、软判决的3类适用于GPU处理的LDPC码纠错并行算法，并对比了3类算法的复杂度、纠错性能以及对雷达信号处理的影响；最后，给出了GPU并行实现方案，对比了算法的实时化效果。仿真与实测结果论证了相较于其他算法，软判决并行算法具有优越的纠错性能和实效性。

Abstract:

Low-Density Parity-Check code(LDPC) decoding is one of the key steps in reference signal reconstruction of passive radar. Decoding algorithms can improve data bit errors caused by noise, but with the high complexity. Combining high memory throughput and tremendous computational horsepower of GPU graphics processor, this paper proposes three types of parallel LDPC decoding algorithms suitable for GPU processing based on hard, mixed, and soft decisions. The complexity, decoding performance, and impact on radar signal processing of the three types of algorithms are described; finally, a parallel GPU implementation scheme is given, and the real-time time-consuming of the algorithms is compared. The simulation and measured results verify that the soft decision parallel algorithm is superior to other algorithms on performance and effectiveness.