Optimal nonlinear fi ltering of stochastic processes in rescue radar

O. Sytnik
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Abstract

Subject and Purpose. Smoke, fog, avalanches, debris of collapsed structures and other optically opaque obstacles in both natural and man-made disasters make optical sensors useless for detecting victims. Electromagnetic waves of the decimeter range penetrate well almost all obstacles, reflect from the trapped people and return to the radar receiver. Due to the breathing and heartbeat, the human-reflected sounding signals get the Doppler phase modulation, which is an information signal. These information signals and their properties provide the subject matter for the present research with the aim to create optimal methods and algorithms of random event processing for the prompt location of survivors by rescuers. Method and Methodology. The method of stochastic analysis of the fluctuation Doppler spectra of reflected sounding signals shows that the information signals have properties of conditional Markov processes. Results. The problem of optimal nonlinear filtering of conditional Markov processes entering the radar signal processing unit has been examined closely. An optimal adaptive filter has been proposed to reduce the masking effect of interferences caused by non-stationary noises and sounding signal reflections from stationary objects. The optimality criterion is the minimum mean square error function whose current value is evaluated in real time during the filtering process as the statistics is accumulated. The filter coefficients are calculated by the recurrent, steepest descent algorithm. The real-time work is carried out through the use of fast Fourier transform algorithms. Conclusion. The structure of the optimal adaptive filter to be built into the radar signal processing unit has been developed. Real radar signals have shown that the optimal filtering during the signal processing in systems designed for detecting live people by their breathing and heartbeat facilitates the interpretation of the observed signals. Some spectra of real signals generated by human breathing and heartbeat are presented.
救援雷达随机过程的最优非线性滤波
主题和目的。在自然和人为灾害中,烟雾、雾、雪崩、倒塌的建筑物碎片和其他不透明的障碍物使光学传感器无法探测受害者。分米范围的电磁波能很好地穿透几乎所有的障碍物,从被困人员身上反射回来并返回雷达接收机。由于人的呼吸和心跳,人反射的探空信号受到多普勒相位调制,是一种信息信号。这些信息信号及其性质为本研究提供了主题,旨在为救援人员及时定位幸存者创建随机事件处理的最佳方法和算法。方法和方法论。对反射探空信号波动多普勒谱的随机分析方法表明,信息信号具有条件马尔可夫过程的性质。结果。研究了进入雷达信号处理单元的条件马尔可夫过程的最优非线性滤波问题。提出了一种最优自适应滤波器,以降低非平稳噪声和静止物体测深信号反射干扰的掩蔽效应。最优准则是在滤波过程中,随着统计量的累积,实时求出最小均方误差函数的当前值。滤波器系数由递归最陡下降算法计算。通过使用快速傅立叶变换算法进行实时工作。结论。研究了雷达信号处理单元中最优自适应滤波器的结构。实际雷达信号表明,在设计用于通过呼吸和心跳检测活人的系统中,信号处理过程中的最佳滤波有助于对观察到的信号进行解释。给出了人体呼吸和心跳产生的真实信号的一些谱图。
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