Sigmoid transform-based broadband echo Doppler in impact noise environment and time delay estimation method

Abstract

Aiming at the problem that the fractional-order Fourier transform algorithm in the impulse noise environment is invalid, the invention is designed to suppress the interference of impulse noises basedon the nonlinear transform-Sigmoid transform. The invention provides a novel method for jointly estimating the Doppler frequency shift spreading factor and the time delay of an LFM impulse radar basedon the energy gathering characteristic of the fractional-order Fourier transform. According to the invention, the method comprises the steps of firstly, combining the Sigmoid transform algorithm withthe fractional-order Fourier transform algorithm and providing a Sigmoid-based fractional-order Fourier transform (Sigmoid-FRFT) algorithm; secondly, realizing the joint estimation of the Doppler frequency shift spreading factor and the time delay based on the peak point searching of the Sigmoid-FRFT. The above method does not need any priori knowledge of noises, and has strong tolerance to low signal-to-noise-ratio noises. Experimental results show that the method is relatively high in parameter estimation precision and low in computational complexity under impulse noises.

Description

technical field [0001] The invention belongs to the field of communication and information systems, and in particular relates to a joint estimation of LFM pulse radar broadband echo Doppler and time delay based on Sigmoid transformation in an impact noise environment. Background technique [0002] Pulse radar uses a linear frequency modulation (LFM) signal with a large time-width-bandwidth product to increase the detection distance while ensuring high resolution. Estimation of Doppler frequency shift and multipath time delay of LFM pulsed radar echo signal is a hot issue in radar and sonar signal processing. LFM is insensitive to Doppler frequency shift, has a large time-width product, and can effectively increase the detection distance while ensuring high resolution. It is one of the most commonly used signal forms in current pulse compression system radars, so its parameters It is estimated that it is a hot topic in radar signal processing. At present, scholars have done...

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Problems solved by technology

At present, there have been many research results on this, for example, using FRFT to analyze the LFM signal and proposing a parameter estimation algorithm; respectively using fractional Fourier transform, short-time fractional Fourier transform, fractional correlation and fractional power However, theoretical research and actual measurement results have found that the actual noise of radar, sonar and wireless communication systems contains a large number of pulse components. At this time, the performance of the algorithm based on the assumption of Gaussian noise will be Significant degradation or even failure

[0004] Aiming at the problem of parameter estimation of LFM pulse radar broadband echo signal under pulse noise, some studies have proposed an improved low-order moment ambiguity function to realize parameter estimation; and proposed a fractional power spectrum algorithm based on fractional low-order statistics. The algorithm uses Fractional low-order moments suppress impulse noise, and use fractional-order power spectrum to achieve energy aggregation of LFM signals, which achieves better estimation results, but this method relies on the prior knowledge of noise and has a large amount of calculation

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