| Space Time Adaptive Processing(STAP)can suppress clutter effectively and improve the detection performance of airborne phased array radar. The research on STAP has been performed for more than 30 years. At present, this technique has been gradually applied to airborne phased array radar for moving targets indication (MTI) from the theory research to the practical applications at home and abroad.It is an important task that the clutter has to be suppressed effectively for airborne phased array radar in the complicated environment. However, due to the motion of airborne platform, the ground clutter spectrums are expended in space-time domain, which leads to the target would be submerged into the clutter. So, the traditional one-dimensional filter can not form a notch that matches for the ground clutter, and it can not suppress clutter effectively. If the clutter has the characteristic of space-time-coupling, the Space Time Adaptive Processing is a two-dimensional filter in space-time domain, which has both the temporal degrees of freedom and the spatial degrees of freedom; the coincidence probability is very small between the clutters and targets, so it can suppress ground clutter perfectly and improve the performance of the moving targets indication. Therefore, STAP becomes a key technique in airborne phased array radar for clutter suppression.Focusing on the STAP applying to airborne phased array radar and the related problems of airborne radar for reduced-rank, suppress clutter and MTI, the dissertation presents and improves some signal processing algorithms. The main contents of the dissertation are described as following.1. Chapter 2 study the relationship between the clutter distribution of phased array airborne radar and its radar system parameters. In succession, we specifically analyzes the general principle of STAP and reduced rank (RR) STAP, the means of JDF$A and JRF$A is presented, which shows that the result will be probably near as the full rank STAP.2. Chapter 3 specifically analyzes the clutter spectrum depends highly on range for forward-looking radar, which results in heterogeneous ground clutter and inaccurately estimation of clutter covariance matrix in space-time adaptive processing (STAP), we propose four approaches to mitigating the effect of the range dependence. These methods are spatial steering vector fitting, clutter-subspace, series expansion and propagator, which use the coherent signal method to compensate the clutter spectrum and the result shows these means reduce the computational load.3. Chapter 4 study the clutter spectrum compensation in the squint radars. In order to mitigate the influence of isolated interference on the covariance matrix estimation, we use the non-homogeneity detector (NHD) to remove these interferences in the preprocessing data. The method starts by transforms clutter returns from element-pulse domain into element-Doppler domain by Chirp z-transform (CZT), which can improve the efficiency of spectrum samples, and has lower computational burden of spectrum analysis than that produced by DFT. Following that, the spatial steering vector fitting method is used to process the new space-time data that can eliminate the nonstationarity of the ground clutter. However, these means need FFT, so a method of DBU-MWF is presented. This method could process it in the data domain, and reduce the computation load of matrix inversion. A method for compensation of clutter spectrum base on similar measure, which the similarity for spectrum structure by a set of values defined by the inner product between the steering vector of range bin under test and of adjacent range bins.4. Chapter 5 studies the STAP application to bistatic airborne radar. According to the clutter model, this dissertation specifically analyzes the relationship between the bistatic clutter distribution and the bistatic geometry. Under the chapter 3 studies, this chapter uses the spatial steering vector fitting means to compensate the clutter spectrum for the first two schemes.
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