Research On Key Techniques Of Sea Clutter Modeling And Radar Signal Simulation System

Sea clutter impacts seriously on the effect and efficiency of maritime surveillance radars. The research on sea model is of great significance for optimum detection algorithm design and performance prediction. The study of characteristics of sea clutter is very important for design of radar system, signal processing of radar, detection of targets on sea surface and remote sensing, etc. The characteristics of sea clutter used to be studied only with statistic theory for years. With the development of new theories and techniques, people try to find better methods to study sea clutter. This paper aims to study some important problems of clutter modeling and simulation, which include as follow:According to the principle that each quadrature component of K-distributed clutter can be modeled, exactly or approximately, by a weighted sum of products of two independent Gaussian variables, a new method for modeling and simulation of correlated coherent K-distributed clutter is presented. Compared with zero memory non-linearity (ZMNL) and spherically invariant random process (SIRP), this method can generate correlated coherent clutter with arbitrary complex auto-variance function. Besides, it doesn't need resolving non-liner equation, so that, the speed of simulation is improved markedly.The non-stationary feature of the sea clutter, i.e., sea spike, is investigated further. Sea spike is redifined from the aspect of time, frequency and energy and based on that space, time and frequency methods for sea spike statistice analyses are presented, which provide quite systematic tools and method to analyse and understand the non-stationary feature further.The continuous hidden Markov model (CHMM) is used to model and analyze the sea clutter. The echoes from sea surface are divided into three CHMM states , Stationary Sea Clutter, Sea Spike and Target. The Gaussian Mixture Density Model (GMDM) and the Baum-Weleh Algorithm are used to construct the Probability Distribution Function (PDF) of the observations of the three states and re-estimate the CHMM parameters, respectively. Meanwhile, the expressing of the Observation-State Joint Probability is modified to avoid the underflow of the denominator during the iterative procedure of the GMDM parmeters. Therefore, a new method is proposed for modeling and analyzing sea clutter.The Non-fully Developed Full-range Sea Spectrum (NDFS) is reconstructed, and a Fractal Sea Model based on NDFS (NDFFM) is presented, which can reflect the real features of sea surface better. The two-scale method is used to calculate the backscattering cross-section of the NDFFM sea surface, and the relationship between the model parameters and the backscattering cross-section is discussed in detail. Compared with the conventional fractal model, this model can fit the real data more exactly, so it is proved to be more accurate and efficient.This paper explicates the theories of modeling and simulating the radar clutter and present a system of radar target-clutter simulator based on direct digital synthesis (DDS) technology.This simulator was implemented by mixed means of software and hardware, and it can agilely generate many kinds of radar clutter with different waveforms, including grand clutter, sea clutter and foil-strip clutter.