基于自适应尺度变换-双稳态随机共振模型的BPSK信号检测算法

为提升在强噪声背景下对二进制相移键控(binary phase shift keying, BPSK)信号的检测性能, 针对主流方法在抑制噪声过程中信号受到一定程度的削弱、信号处理系统引入新噪声导致检测性能下降的问题，提出了基于自适应尺度变换双稳态随机共振模型的BPSK信号检测算法。对于经典的双稳态随机共振系统只能处理小幅度、低频段的周期信号的情况, 首先将双稳态随机共振系统进行尺度变换, 证明在高采样率条件下, 双稳态随机共振系统可应用于高频的BPSK信号, 并基于Neyman-Pearson准则设计了非线性阈值检测系统, 推导且定量表示出检测器的误码率, 以此作为反馈量, 自适应地调节系统参数, 构建了信号检测的完备流程。通过仿真实验验证了尺度变换的可行性以及所提算法的适用性, 为低信噪比条件下的弱BPSK信号检测提供了理论依据。

Detection algorithm of BPSK signal based on adaptive scale change-bistable stochastic resonance model

In order to improve the detection performance of binary phase shift keying (BPSK) signals under the background of strong noise, with the signal of the mainstream methods weakened to a certain extent in the process of noise suppression and the signal processing system introducing new noises, which leads to the decline of detection performance, a BPSK signal detection algorithm based on adaptive scale transformation of bistable stochastic resonance model is proposed. The classic bistable stochastic resonance system can only handle small amplitude and low frequency periodic signals, In view of this, we first carry ont bistable stochastic resonance system scale transformation, proving that under the condition of high sampling rate, bistable stochastic resonance system can be applied to the high frequency of BPSK signal. Based on Neyman-Pearson criterion, a nonlinear threshold detection system is designed, and we quantitatively indicate the error rate of detector as a feedback, adaptively adjust system parameters, and construct the complete process of signal detection. The feasibility of scale transformation and the applicability of the proposed algorithm are verified by simulation experiments, which provides a theoretical basis for weak BPSK signal detection under the condition of low signal to noise ratio.