Detection And Parameter Estimation Of Maneuvering Target Under The Circumstance Of Short Coherent Processing Interval

If the target is a maneuvering one, its Doppler frequency of echo signal changes with time in the Coherent Processing Interval(CPI). This change makes it difficult to accumulate the power of target for conventional Space-time Adaptive Processing(STAP) methods and leads to the performance of maneuvering target detection degrade. For the maneuvering target with a constant acceleration, its echo can be approximately regarded as a Linear Frequency Modulation(LFM) signal. It needs more pulses for maneuvering target detection and parameter estimation by utilizing the time-frequency analysis methods, otherwise the parameters estimation precision is difficult to meet the requirements. The pulse number transmitted by the airborne radar is limited in a single CPI. The limited pulse number causes the coherent processing time shorten when the Pulse Repetition Frequency(PRF) is constant.So it is difficult to adopt the time-frequency analysis methods directly in the study of maneuvering target detection and parameter estimation when the coherent processing time is short. In order to solve this question, the corresponding algorithms are proposed in the paper.They can acquire accurate maneuvering target parameter estimation results in a short coherent processing time.The main contributions and innovations of this dissertation are as following:Firstly, the echo data model received by the airborne radar are introduced. Then the echo signal model of the maneuvering target is derived through the description of maneuvering target echo signal.Secondly, a novel algorithm intending to detect and estimate the parameters of air maneuvering target by means of reconstructing time samples and signal is proposed in this paper. It can acquire precise parameter estimation under the circumstance of short CPI via reconstructing time samples and signal. Its effectiveness is verified through the numerical simulations compared with Cramer-Rao Bound.Thirdly, a novel and low complexity algorithm for parameter estimation of maneuvering target is proposed based on compressive sensing and Cubic Phase Transform(CPT). The proposed algorithm can not only sample the signal at a lower rate than Nyquist sampling theorem, but acquire precise parameter estimation with limited pulses in a single CPI for airborne radar.Finally, the Cramer-Rao bounds for the maneuvering target in airborne radar are derived to verify the effectiveness of the proposed algorithms in this paper.