Parameter estimation method for low signal-to-noise ratio signal

Abstract

The invention provides a parameter estimation method for a low signal-to-noise ratio signal, which comprises the following steps of: processing a to-be-detected noisy signal by using a nonlinear stochastic resonance method, transferring noise energy to signal energy, and effectively recovering signal waveform information. The proposed segmented bistable stochastic resonance solves the classical stochastic resonance nonlinear gain problem, realizes the amplitude linear gain, and solves the amplitude gain coefficient. The signal frequency and amplitude information submerged by noise can be effectively extracted, the signal frequency and amplitude information can be accurately estimated in a low signal to noise ratio environment, and the method is a signal parameter estimation method which isremarkable in anti-noise effect and has good estimation performance.

Description

technical field [0001] The invention relates to the field of signal parameter estimation, in particular to a method for parameter estimation using a stochastic resonance method. Background technique [0002] In scientific research and industrial production activities, people need to extract useful information from the observed results, but due to the complexity of the environment and the limitation of observation means, the information we need is often overwhelmed by noise and cannot be obtained, especially in In the military field, with the development of stealth technology for ships and other equipment, the useful parameters of the target are submerged by ocean noise, which poses a great threat to national defense security. Therefore, the correct estimation of signal parameters has important research value and significance. [0003] At present, many methods have been produced for the estimation of signal frequency parameters, including various filters, which can achieve c...

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Problems solved by technology

[0003] At present, many methods have been produced for the estimation of signal frequency parameters, including various filters, which can achieve certain effects, but in the estimation method of signal amplitude parameters Research is currently less

The root mean square method can obtain higher-precision signal amplitude through complex calculations. The maximum likelihood estimation method uses a one-dimensional search with a large amount of calculation to jointly estimate the signal frequency, phase, and amplitude and can obtain high estimation accuracy. Gaussian Newton's recursive method can also give a good estimate of the signal amplitude but requires a known signal frequency

However, various existing signal parameter estimation methods, including the above-mentioned methods, require a high signal-to-noise ratio to achieve a certain effect when estimating signal parameters, especially when estimating signal amplitude.

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