Line Spectrum Estimation Method Based on Approximate Message Passing
An approximate message and message passing technology, applied in the field of online spectrum estimation, can solve the problems of limited signal-to-noise ratio of detection data, degradation of algorithm performance, inability to accurately estimate signal frequency and complex amplitude, etc., and achieve the effect of accurate estimation
Active Publication Date: 2022-04-15
GUANGDONG UNIV OF TECH
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Problems solved by technology
[0009] The present invention aims to solve the problem that the signal frequency and complex amplitude cannot be accurately estimated when the detection data is incomplete and the signal-to-noise ratio is limited in the prior art, and the performance of the algorithm is degraded when a low-resolution analog-to-digital converter is used, and it is impossible to accurately estimate For problems such as model order K, a line spectrum estimation method based on approximate message passing is provided
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Embodiment 1
[0063] like figure 1 As shown, the line spectrum estimation method based on approximate message passing includes the following steps:
[0064] S1. Construct a line spectrum estimation model, expand the model order K of the line spectrum estimation model and introduce a logic sequence s;
[0065] S2. Initialize the estimated value of the signal frequency and the estimated value of the signal complex amplitude of the line spectrum estimation model, preset the number of iterations, and obtain the detection data Y;
[0066] S3. According to the detection data Y and the factor diagram of the line spectrum estimation model, the approximate posterior probability of the signal frequency, the approximate posterior probability of the signal complex amplitude, and the logic sequence s are respectively obtained through the message passing method based on expectation propagation and the circular belief propagation rule The nth variable s in n The approximate posterior probability of ;
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The invention relates to the technical field of line spectrum estimation, and discloses a line spectrum estimation method based on approximate message passing, including: constructing a line spectrum estimation model, expanding the model order K and introducing a logic sequence s; initializing the estimated value of signal frequency and signal complex amplitude , the number of iterations is preset, and the detection data Y is obtained; according to the detection data Y and the factor graph, the signal frequency, signal complex amplitude and the nth variable s in the logic sequence s are respectively obtained n The approximate posterior probability of the three; according to the approximate posterior probability of signal frequency and signal complex amplitude, the estimated values of signal frequency and signal complex amplitude are respectively obtained; according to s n The approximate posterior probability of the model order is obtained by repeating the last two steps until reaching the preset number of iterations, the estimated value of the output signal frequency and signal complex amplitude, and the model order. The present invention uses the message transfer method based on expectation propagation and the least mean square The error estimation method accurately estimates the signal frequency and signal complex amplitude; by defining the log likelihood ratio, the model order K is accurately estimated.
Description
technical field [0001] The present invention relates to the technical field of line spectrum estimation, and more particularly, to a line spectrum estimation method based on approximate message passing. Background technique [0002] The line spectrum estimation problem refers to the superposition parameters of the complex exponential function extracted from the data affected by noise or quantized by a low-precision quantizer, which is used in the distance and direction estimation of sonar and radar, channel estimation in wireless communication, and array signal processing. Both DOA estimation and beamforming are involved. [0003] In the online spectrum estimation problem, the detection data Y is obtained from the original signal of K complex sinusoidal superposition through M sensors and L snapshots, and its composition can be expressed as: [0004] [0005] Among them, θ represents the frequency, A(θ) represents the vector formed by the complex exponential function of ...
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IPC IPC(8): H04L25/02
CPCH04L25/0256
Inventor 张浩川李祉延
Owner GUANGDONG UNIV OF TECH