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An effective estimation of time-dependent Doppler frequency for weapon fuzing

Proximity sensing is required for a wide range of military applications, especially for weapon fuzing. In this paper, wavelet video processing is discussed which is used for proximity sensing of objects through their time dependent Doppler shift. A continuous wavelet transform is performed on the Doppler signal, after subjecting it to a time varying window, the signal features are extracted from resulting wavelet video. This is used as input to pattern recognition neural networks. The networks are trained to estimate the time varying Doppler shift from extracted features. When the Doppler shift reaches its optimum value the warhead will be initiated for optimum detonation.