New Methods of Simulating Radar Clutter Return Arrays

Acquiring and recording clutter return data in a radar station is a crucial approach but a high price must be paid. Simulating various radar clutters through computer operation is an efficient approach and not much price is paid in a radar laboratory nowadays. Based on three common U(0,1) random sources from Fortran, MatLab, and chaotic Logistic programs, we compare their statistics: autocorrelation, cross-correlation, probability densities, etc. Fortran U(0,1) is found to be a better random source for our sake. Based on the study of uniform-and staggered-PRI (pulse repetition interval) waveforms, coherent transmitting and receiving, pulse compression technology, etc., we propose three algorithms, LU matrix decomposition, FIR (finite impulse response) filtering interpolation, and IIR (infinite impulse response) filtering, for simulating range-azimuth clutter arrays, which engage conventional characteristics: uniform or staggered PRIs and Doppler spectra. Their mathematic equations and algorithm computations are described. Many simulation tests are achieved to verify the validity and effectiveness of the algorithms; the clutter arrays with a few radar signal characteristics are demonstrated. Furthermore, through the study of two-type pulse compressions, phase code and LFM (linear frequency modulation), and large time-width pulse wave’s backscattering, we create a mechanism of discrete and continuous dynamical systems forming the pulse compression clutter returns, then simulate the composite clutter arrays, which characterize pulse compression over range cells and the Doppler spectra over azimuth cells with staggered PRIs. Finally, we discuss combination algorithms for nonstationary radar clutter arrays, which have two typical models of nonstationary environments, continuously-varying spectral parameters, and step-varying translation of backscattering regions.