A Cubic Phase Signal Parameter Estimation Method Based on Cyclic Shift

Abstract

The invention relates to the technical field of cubic phase signal parameter estimation, and relates to a method for estimating cubic phase signal parameters based on cyclic shift. The specific steps are: 1) finding the instantaneous autocorrelation function of the discrete cubic phase signal; 2) using NUFFT to quickly realize the signal 3) Carry out parameter space transformation and cyclic shift accumulation operation to the obtained time-frequency distribution; 4) Utilize the peak detection technology to simultaneously complete the joint estimation of frequency modulation frequency and secondary frequency modulation frequency; the present invention significantly reduces the cubic The complexity and calculation amount of phase signal parameter estimation avoids error transmission in the process of estimating individual parameters one by one, gets rid of the complicated two-dimensional spectrum peak search process, and improves the estimation accuracy and processing efficiency of the system.

Description

technical field [0001] The present invention relates to the technical field of cubic phase signal parameter estimation, and more particularly, the present invention relates to a method for estimating cubic phase signal parameters based on cyclic shift in the technical field of radar target detection and parameter estimation. Background technique [0002] In practical engineering technology applications such as radar, sonar, wireless communication, geological exploration and medical imaging, most signals have non-stationary characteristics, and their phases are also continuous and instantaneous. Therefore, the polynomial phase signal has become the most common and widely used signal model for signal processing in this field. [0003] The phase parameter of a polynomial phase signal contains important information. In radar signal processing, the primary phase, secondary and tertiary phase parameters correspond to the initial velocity, acceleration and acceleration rate of hig...

AI Technical Summary

Problems solved by technology

The defect of this type of method is that the multi-component cubic phase signal parameters are estimated sequentially from high-order to low-order, and the estimation performance of low-order phase parameters depends on the accuracy of high-order parameter estimation, which will cause serious error transmission (Error Propagation) effect

In addition, such methods use Fourier transform for non-uniform sampling data, and cannot use FFT to quickly complete the corresponding Fourier transform, and will have a certain impact on the estimation accuracy of parameters.

The DCFT algorithm for cubic phase signals does not produce cross-term problems. Its shortcoming is that it realizes the estimation of modulation frequency and quadratic modulation frequency through two-dimensional search. The search process will lead to a huge amount of calculation and increase the complexity of the system.

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