Double-subsegment phase difference frequency estimation method and device adopted by method

Abstract

The invention discloses a double-subsegment phase difference frequency estimation method and a device adopted by the method. The method comprises the steps of taking first subsegments and tail subsegments in 2N-1 samples x(-N+1)-x(N-1) to form double subsegments; respectively performing FFT transformation on x0 and xN-1 to obtain corresponding peak value spectrums; performing simple linear treatment on a peak value spectrum phase (shown in description) difference value to obtain a frequency estimation result. The device comprises an analog-digital converter, a DSP device and a driving and displaying module, wherein signals x(t) to be detected are sampled through the analog-digital converter to obtain a sample sequence x(n), the sample sequence is fed into the DSP device in a parallel digital input mode, and parameter estimation of the signals is achieved through internal algorithm processing of the DSP device. Finally, the frequency estimation result and theoretical mean square errors of frequency estimation are displayed through the driving and displaying module. The double-subsegment phase difference frequency estimation method and the device are small in computation amount, and the estimation method is simple, high in efficiency and low in resource consumption, and the hardware cost is greatly saved.

Description

technical field [0001] The invention relates to the field of digital signal processing, in particular to a dual-sub-segment phase difference frequency estimation method and a device thereof. Background technique [0002] The frequency parameter measurement of signals is a crucial issue in signal processing in the fields of radar communication, sonar, speech processing, fault diagnosis and even medical diagnosis and treatment, which has attracted widespread attention of relevant scholars at home and abroad. Among them, the frequency estimation of the complex exponential signal in the background of white noise is the basic problem of signal processing, and it is also the [1] , array signal processing [2] and vibration analysis [3] core issues in the field. For example, in the continuous wave radar speed measurement system, in order to measure the instant running speed of the moving target, it is necessary to realize high-precision measurement of the frequency (ie Doppler fr...

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Problems solved by technology

[0005] However, literature [12] pointed out that most estimates based on interpolation estimation and spectral correction method are nonlinear biased estimators, such as Quin interpolation estimator [13,17] , Macleod interpolation estimator [15] , Provencher interpolation estimator [18] , Candan interpolation estimator [12,16] and ratio correction [11] , Energy center of gravity correction method [19] etc., the estimation principles of these methods are mathematically approximated (only when the number of DFT points N is large enough, the approximation error can be ignored), so even in the case of no noise, there are deviations in the frequency estimation, and the errors are not large. is 0

In addition, because the frequency estimation method is limited by nonlinear factors, the measurement accuracy of the literature [11,13,15,17-19] also needs to be improved, and the theoretical expression of the frequency estimation variance has not been derived

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