Micro-Doppler analysis of ballistic targets

Nowadays the challenge of the identification of ballistic missile (BM) warheads in a cloud of decoys and debris is essential in order to optimise the use of counter-missile resources. This chapter is aimed at providing ballistic target (BTs) micro-motion models and examples of signal processing tools to handle this family of targets. The chapter introduces signal models for both warheads and decoys of different sizes and shapes. Additionally, an efficient and robust framework is presented, which exploits the microDoppler (μD) information extracted from the time-frequency analysis of the radar echo from the target. Some feature extraction approaches are also presented, including those based on the estimation of statistical indices from the one-dimensional (1D) averaged cadence velocity diagram (ACVD), on the evaluation of pseudo-Zernike (pZ) and Krawtchouk (Kr) image moments and on the use of two-dimensional (2D) Gabor filters, considering the CVD as 2D image. An assessment of the presented algorithms is also reported in this chapter exploiting real radar data realised in a laboratory.