船用雷达目标跟踪的新方法

A Novel Method of Marine Radar Target Tracking

本文提出一种由广义小波神经网络实现船用雷达跟踪中航迹外推的自适应新方法 .由S(sigmoid)函数构造的尺度函数和小波作为网络中神经元的激励函数 ,隐层节点数由小波分解次数和处理信号维数决定 ,输出层采用局部连接方式以解决多维信号的不利影响 .理论证明 ,广义小波神经网络的鲁棒性在一定条件下优于BP网络 .仿真表明 ,该方法的在线处理运算量不随所跟踪的运动目标模型的复杂性而增加 ,并且对变加速和急转弯运动目标具有较高的跟踪精度 .

This paper presents a novel adaptive method to predict the next point of target on line by means of general wavelet neural network.The scaling function and wavelet constructed by the sigmoid function are used as the active function in the network.The number of hidden units is determined by the number of wavelet decomposition and the dimension of input signal.The local connection is used in the output layer to destroy the influence of multi dimension signal processing.It is proved that the robust property of the wavelet network is better than that of BP network in certain conditions.Simulation shows that the computational cost of this method does not increase with the complexity of the model of moving target.Moreover,the method has the higher tracking accuracy for the moving targets with variable acceleration and quick turn in a corner.