| Unlike high frequency SAR/GMTI systems, low frequency UWB SAR/GMTI system has large beamwidth, which makes moving target signal disperse to a large angle range and results in a low input SINR. Besides, its long wavelength is less sensitive to range velocity of the moving target. So it is difficult to detect moving target using UWB SAR/GMTI system.This paper invested the long CPI STAP technique for moving target detection using low frequency UWB SAR/GMTI. Unlike traditional short CPI STAP, the long CPI STAP can endure the range walk between range bins, thus can achieve higher output SINR and better performance of moving target detection.The long CPI space-time spectrum of moving target and clutter is first analyzed, which can serve as the basic principle of long CPI STAP. Then a basic long CPI STAP model is proposed, which involves three-dimension samples from space, slow time, and fast time.By transforming the basic long CPI STAP model to frequency-Doppler domain, the optimal frequency-Doppler domain long CPI STAP filter is introduced In Chapter 3 of the dissertation. Then the dimension of the model is optimal reduced based on the statistic independence characteristic of clutter in different frequency-Doppler bins. After this operation, the frequency-Doppler domain long CPI STAP can be reduced to two steps:"local STAP"and"coherent integration of local STAP"in frequency-Doppler domain. The former step is done in each frequency-Doppler unit, while the latter one requires selecting the output of frequency-Doppler local STAP corresponding to certain velocity and then coherent integration is realized applyingω-k imaging algorithm. Both the two steps can be designed as forms independent of position parameter of the moving target, which make it possible to calculate the output long CPI STAP simultaneously for all moving target in different position of the scene. Moreover, a moving target detection flow for frequency-Doppler domain long CPI STAP is proposed.By transforming the basic long CPI STAP model to image domain, the optimal image domain long CPI STAP filter is introduced in Chapter 4 of the dissertation. This model involves three-dimension of space-azimuth-range, thus can adapt the defocusing phenomenon of the moving target in UWB SAR image. Based on the statistic independent characteristic of clutter in different pixels, the optimal image domain long CPI STAP filter can be reduced to single-pixel or multi-pixel reduced-dimension filters.After this operation, the image domain long CPI STAP contains two steps as"local STAP"and"coherent integration the output local STAP"in image domain. Both the two steps can be designed as forms independent of position parameter of the moving target. The local STAP is done in each pixel along its multi-channel observations. We propose image domain local STAP technology in ideal environments, nonhomogeneous environments."Coherent integration local STAP in image domain"requires is done by first selecting the output of image domain local STAP corresponding to certain velocity, and then transforming to two-dimension wavenumber domain to compensated defocusing. Building on the ground work above, a moving target detection flow for image domain long CPI STAP is proposed. Its predictive performance is also given.By transforming the basic long CPI STAP model to subaperture-image domain, the optimal subaperture- image domain long CPI STAP filter is proposed in Chapter 5 of the dissertation. Using the statistic independent characteristic of clutter in different subaperture, this model has its reduced-dimension form, which contains two independent steps as"subaperture STAP"and"coherent integration the output of subaperture STAP". Both the two steps can be designed as forms independent of position parameter of the moving target. A multi-resolution moving target detection method based on subaperture image domain STAP is proposed, which combines different number of subapertures to realize moving target detection. The method combines the merits of short CPI for fast moving target detection and long CPI for slow moving target detection.Throughout Chapter 3 to Chapter 5, the three long CPI STAP methods are validated and their performances are valuated based on the same half-real triple-channel low frequency UWB SAR data. The results show that the frequency-Doppler domain long CPI STAP method can be applied to the conditions that the moving target's range walk across range cell both in slow time domain and channel-dimension. The method also exploits the large relative bandwidth of the system to eliminate blind velocity and repeated detection caused by sparse placed antennae. The image domain long CPI STAP method has better adaptability for nonhomogeneous clutter environment. The subaperture image domain long CPI STAP method gets the ability of multi-resolution moving target detection, having the advantages of high time-resolution from short CPI STAP and good moving target detection performance from long CPI STAP.When estimate the moving target's parameters directly based on long CPI STAP, the estimation accuracy is limited by sample interval of search parameters and length of baseline. In Chapter 6 of the dissertation, we research on the parameter estimation technology and propose a complete method for moving target parameter estimation based on long CPI STAP. Combining long CPI STAP with the concept of auto-focusing and ATI, this method can reach high parameter estimation accuracy when using sparse research interval and short baseline.
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