基于随机共振的惯性传感器信号实时处理方法

根据惯性传感器信号处理特点,研究其基于随机共振的信号实时处理方法。首先,从实时性的角度出发,确定随机共振数值算法--龙格库塔法,并对其进行相应改进,实现实时处理。然后,研究单稳系统中各个参数对信号恢复结果的影响,确定系统处理的较佳参数。最终的仿真结果表明，静态信号的零漂值得到了较大改善,而动态信号的信噪比最大可提高约20 dB。同时,为了进一步验证算法,在数字信号处理硬件平台上实现算法,采样频率为5 000 Hz,结果完全能够满足惯性传感器信号处理的要求。因此,所提算法能够有效进行惯性传感器信号实时处理,为随机共振理论在惯性传感器信号处理中的应用提供了重要参考。

Real-time processing method based on stochastic resonance for inertial sensor signals

The inertial sensor signals’ real time processing method based on stochastic resonance is studied. First, according to the real time property, the numerical algorithm of the Runge Kutta method and the corresponding improvements are studied and determined, which solves the problem of real time processing. And then the system parameters’ influence on the recovery of the signals is studied and finally the better parameters of the system are determined. The simulation results show that the static signal zero drift value is greatly improved, and the dynamic signal’s signal-to-noise ratio is increased by about 20 dB. At the same time, in order to further validate the algorithm,the real time processing is implemented by digital signal processor at the sampling frequency 5 000 Hz and the results verify that inertial sensor signal real-time processing requirements can be met. The proposed algorithm can effectively meet real-time processing of inertial sensor signal’s, thereby providing an important reference for the application of stochastic resonance theory in inertial sensor signal processing.