Research On Radar Weak Target Motion Parameter Estimation Based On LFMCW/OFDM Signals

The emergence and rapid development of aircraft such as small drones has brought difficulties to airspace monitoring and control.Radar can search for targets from a wide range of long distances and is one of the important means of unmanned aerial vehicle(UAV)detection.Due to the low speed of motion,small radar cross section and flexible release,the radar's weak target detection capability is challenged under severe interference at low altitude.Based on the detection of UAV,the weak target detection and parameter estimation methods on linear frequency modulated continuous wave(LFMCW)and orthogonal frequency division multiplexing(OFDM)signals are studied according to different radar signals and target motion states.For sawtooth linear frequency modulated continuous wave radar,a phase correction,energy accumulation and parameter estimation method for moving target echo based on approximate maximum likelihood estimation is proposed.For multiple targets with uniform motion,the Keystone transform is used to correct the signal to the same distance cell,and the blind speed matching is used to solve the ambiguous Doppler velocity that may occur in the correction.Combined with the maximum likelihood(ML)model,the approximate maximum likelihood estimator is obtained,and a good parameter estimation result is obtained with less computational complexity.Aiming at the uniform acceleration target,a direct phase difference method combined with CZT is proposed.The simulation experiment verifies the correctness of the theoretical analysis.Aiming at the characteristics of mechanical scanning radar,a multi-frame coherent accumulation method based on phase compensation is proposed.The accumulation performance of target acceleration on echo energy is discussed.The simulation and measured results show that the accumulated energy of the K-frame signal is about K times that of the single-frame signal.For symmetrical triangular linear frequency modulated continuous wave radar,a target detection and motion parameter estimation method based on phase compensation and two-dimensional frequency domain SK-CFAR detector is proposed.With Zoom-FFT process,the local compensation method is adopted to analyze only the frequency domain near the target spectrum of the up-chirp signal,while the range migration and Doppler diffusion caused by the target motion are solved,which effectively reduces the calculation amount in the search process,and obtains better target detection performance under a certain input signal-to-noise ratio.In order to avoid the interference of the target to be detected,the two-dimensional frequency domain SK-CFAR detector is constructed,and the neighboring interference target is accurately deleted according to the constant skewness,which greatly improves the detection capability of the target.Aiming at the characteristics of uniform(acceleration)signals,a method based on phase compensation and local template matching is proposed.The simulation results show that the required input signal-to-noise ratio is improved by about 3dB compared with the local compensation method,which has certain advantages in weak target detection.Finally,this paper studies the moving target parameter estimation problem based on PC-OFDM signal.According to the multi-carrier orthogonal structure of OFDM signal,a parameter estimation method based on channel separation and Keystone transform is proposed.The approximate maximum likelihood estimator of multi-objective motion parameters is obtained by combining ML model and CLEAN technique.It can be known that the algorithm has a comprehensive advantage in terms of computational complexity and estimation accuracy.