基于改进卡尔曼滤波的水声通信盲自适应多用户检测算法

Blind Adaptive Multi-User Detection Method for Underwater Acoustic Communication Based on Improved Kalman Filter

摘要:

针对水声通信网络中遇到的多用户检测中目标用户的多址干扰等检测问题,提出了基于改进Kalman算法的盲自适应多用户检测算法,解决了多用户检测中的多址干扰对水声通信信道用户变动时的干扰抑制问题；仿真分析分别针对同步多用户、异步多用户通信过程,对比了传统Kalman算法及改进的Kalman算法的性能差异,通过仿真对比表明,改进后的Kalman检算法不需要训练序列即可以实现同步和异步通信状态下的多水声目标用户的盲自适应检测,改进后的算法目标检测的信干比比传统算法最大可提高6 dB；新算法对于水下多用户检测、区分,准确、稳定的实现基于CDMA协议的快速水声通信具有重要意义。

Abstract:

In order to solve multi access interference (MAI) effect of multi-user blind detection in underwater acoustic communication networks, blind adaptive multi-user detection method based on improved Kalman filter algorithm was proposed. This method can suppress the MAI problem when the user number increases. Simulation was done for both traditional Kalman method and improved Kalman method in synchronous and asynchronous multi-user communication case, the simulation results show that the improved Kalman detection algorithm does not require training sequences that can realize synchronous and asynchronous communication state of multiple underwater acoustic target users of blind adaptive detection, improved Kalman filter algorithm can get higher SIR in target detection than the traditional algorithm by 6 dB in maximum. The new algorithm is of great significance for accuracy and stability of underwater acoustic communication based on CDMA protocol in multiuser detection and differentiation. 