Clutter Reduction and Target Detection Enhancement Using Wavelet Transform Techniques

We propose to develop novel techniques that enhance the detection and indentification of cluttered targets using wavelet transform (WT) techniques. Two approaches will be explored. The first approach characterizes various clutters by suitably selected wavelet packets such that the WT coefficients are contributed mostly by clutter information but almost not affected by the targets. Bu subtracting these WT coefficients from the original signal, the clutters are effectively suppressed and thus the target detection can be greatly enhanced. The second approach is the wavelet matched filter which is synthesized wth reference data and wavelet packets that represent the features of the target. The wavelet matched filter incorporates the efficient feature detection and noise suppression capability of the WT and high discrimination ability of the matched filter. The clutter reduction and target identification operations are performed in a single step. The performance of the developed alforithms and the hardware implementations will also be investigated.