Application of microaccelerometer in target recognition

Abstract

The paper presents a application method of detecting moving ground target based on micro accelerometer. Because vehicles moving over ground generate a succession of impacts, the soil disturbances propagate away from the source as seismic waves. Thus, we can detect moving ground vehicles by means of detecting seismic signals using a seismic tranasducer, and automatically classify and recognize them by data fusion method. The detection system on the basis of MEMS technology is small volume, light weight, low poer, low cost and can work under poor circumstances. In order to recognize vehicle targets, seismic properties of typical vehicle targets are researched in the paper. A data fusion technique of artifical neural networks (NAA) is applied to recognition of seismic signals for vehicle targets. An improved back propagation (BP) algorithm and ANN architecture have been presented to improve learning speed. The improved BP algorithm had been used recognition of vehicle targets in the outdoor environment. Through experiments, it can be proven that target seismic properties acquired are correct. ANN data fusion is effective to solve the recognition problem of moving vehicle target, and the micro accelerometer can be used in target recognition.