Target Parameter Estimation Based On The Fractional Fourier Transform In Bistatic MIMO Radar System

Target parameter estimation is an important aspect in radar signal processing, which has been widely used in radar, sonar, wireless communication positioning system, radio monitoring and military fields. In recent years, target parameter estimation in bistatic MIMO radar system has attracted more and more attentions, but Doppler frequency was ignored or assumed as time-invariant in most existing models. In fact, due to the velocities and moving directions of targets varying constantly, the received signals contain Doppler frequency with time-variant. If Doppler frequency is assumed as time-invariant, the performance of parameter estimation will degrade. To overcome the drawbacks of traditional models and methods, this dissertation mainly studies the model for received signals and the target parameter estimation methods under different noise environments in bistatic MIMO radar system. The main contributions are listed as follows:(1) Since a narrow received signal contains time-varying Doppler frequency, this dissertation proposes a signal model with linear time-varying Doppler frequency. For this signal model, by the fractional Fourier transform (FRFT), two approaches and the fractional power spetrum density are proposed to estimate target parameters in the Gaussian noise environment. This dissertation, combining fractional lower order statistics (FLOS) and fractional power spectrum, proposes a novel approach to precisely estimate target parameters in the impulsive noise environment. Furthermore, the Cramer-Rao bound for target parameter estimation is derived. Due to three dimensional motion characteristics of the target, the received signal may contain nonlinear time-varying Doppler frequency. We propose an extented signal model, then propose the fractional ambiguity function (FAF) algorithm and the FLOS-FAF algorithm to accurately estimate target parameters in both Gaussian and impulsive noise environments.(2) Since the wideband echo signal, in comparison with the transmitted signal, often contains time delay and Doppler stretch, which can not be estimated availably by the narrowband model, this dissertation proposes an extented wideband received signal model, then FRFT based algorithm and fractional power spectrum density algorithms are proposed to estimate jointly target parameters in the Gaussian noise environment. Then the FLOS-FPSD algorithm is applied for target paramters estimation of wideband signal model, which accurately achieves target parameter estimation and localization in the impulsive noise environment. Furthermore, the Cramer-Rao bound for target parameter estimation is derived and computed in closed form which shows its good performance.(3) For the difficulty on collection of moving information on a civil airplane, this dissertation proposes an extented model for received signals. We combine FAF and the projection approximation subspace tracking (PAST) algorithm and propose the FAF-PAST method to achieve airplane parameter dynamic estimation in the Gaussian noise environment. Furthermore, the FF-RLM-PAST algorithm based on FLOS-FAF method is proposed to estimate airplane parameters in the impulsive noise environment, which effectively suppresses the impulse noise and achieves parameter dynamic estimation of airplane accurately.