| With the rapid development of wireless communication,radar,sonar,remote sensing and other fields,higher requirements are put forward for high-precision and high-reliability signal transmission and ranging technology.Linear frequency modulation(LFM)signal is a kind of non-stationary signal,which has the advantages of long distance,strong noise immunity and large time-bandwidth broad product,LFM signal is widely used in high-precision ranging technology.However,the inevitable noise interference in these engineering fields,especially under the impulse noise interference,significantly degrades the performance of traditional signal ranging methods,which seriously affects the ranging effect.In order to solve the problem,this paper carries out the research on signal ranging methods in the background of impulse noise,focusing on the noise suppression method based on tracking differentiator to achieve effective suppression of impulse noise,reduce the impact of noise interference on ranging results,and use the Fractional Fourier Transform based ranging method to extract useful information of the signal in order to achieve the purpose of accurate ranging.The main study of this paper is as follows:(1)Starting from the LFM signal model,the a stable distribution model used to describe the actual impulse noise interference is analyzed,the LFM radar ranging principle is studied,and the echo signal is simulated and analyzed,laying the foundation for further research on the echo signal noise suppression algorithm.(2)To address the problem that a large amount of impulse noise drowns the signal in the echo signal,resulting in the subsequent Fractional Fourier Transform ranging algorithm cannot extract useful information from the signal,this paper proposes a sliding window-based tracking differentiator noise suppression algorithm(sliding window TD),which combines the Tracking Differentiator with the sliding window and adaptively adjusts the tracking factor within the sliding window to achieve the suppression of noise in the echo signal.Simulation experiments show that the proposed sliding window TD algorithm has the smallest root mean square error compared with the tracking differentiator noise suppression algorithm and the median filter algorithm in the ranges of 1.0≤α≤1.8,GSNR=1dB and α=1.5,-3dB≤GSNR≤4dB.It provides an effective solution to achieve noise suppression in the echo signal.(3)In this paper,based on the impulse noise suppression of the echo signal,we carry out research on the Fractional Fourier Transform(FRET)ranging method of the LFM signal as the transmit signal to achieve the ranging of the target.The simulation experiments show that in the range of 1.0≤α≤1.8,GSNR=1dB,the target distance is set to 268m,and the comparison algorithms have all failed,while the sliding window TD-FRFT algorithm can extract the useful information of the echo signal to achieve ranging,and its root mean square error of ranging is kept at 0.4748m.For the problem that DFRFT discrete equal interval sampling produces fence effect and reduces the estimation accuracy of the peak point of the echo signal,this paper adopts Rife algorithm to interpolate the peak point position of the echo signal after FRFT to improve the ranging accuracy.Under the experimental conditions of α=1.0,GSNR=1dB and different target distances,the sliding window TD-Rife-FRFT algorithm has the smallest root mean square error of ranging compared with the comparison algorithm,which proves that the algorithm can effectively improve the estimation accuracy of the target with better performance.(4)In order to test,verify and evaluate the signal processing algorithms and reduce the cost of real-world scenario testing and development,this paper designs and develops a LFM signal ranging simulation system in which the signal processing related algorithms studied in this paper are integrated.Through functional testing and verification of the simulation system,it shows that the system has good user interactivity,can simulate scenarios with different intensity impulse noise and LFM signal,can generate corresponding time-domain,frequency-domain and time-frequency spectrum according to the user’s parameter settings,and can visualize the processing results of the signal processing related algorithms studied in this paper. |
