Power spectral density estimate using covariance method
Estimation / Power Spectrum Estimation
dspspect3
The Covariance Method block estimates the power spectral density (PSD) of the input using the covariance method. This method fits an autoregressive (AR) model to the signal by minimizing the forward prediction error in the least squares sense. The Estimation order parameter specifies the order of the allpole model. The block computes the spectrum from the FFT of the estimated AR model parameters. To guarantee a valid output, the Estimation order parameter must be less than or equal to half the input vector length.
The input must be a column vector or an unoriented vector. It represents a frame of consecutive time samples from a singlechannel signal. The block outputs a column vector containing the estimate of the power spectral density of the signal at N_{fft} equally spaced frequency points. The frequency points are in the range [0,F_{s}), where F_{s} is the sampling frequency of the signal.
Selecting Inherit FFT length from estimation order, specifies that N_{fft} is one greater than the estimation order. Clearing the Inherit FFT length from estimation order parameter allows you to use the FFT length parameter to specify N_{fft} as a power of 2. The block zeropads or wraps the input to N_{fft} before computing the FFT.
When you select the Inherit sample time from input check box, the block computes the frequency data from the sample period of the input signal. For the block to produce valid output, the following conditions must hold:
The input to the block is the original signal, with no samples added or deleted (by insertion of zeros, for example).
The sample period of the timedomain signal in the simulation equals the sample period of the original time series.
If these conditions do not hold, clear the Inherit sample time from input check box. You can then specify a sample time using the Sample time of original time series parameter.
See the Burg Method block reference for a comparison of the Burg Method, Covariance Method, Modified Covariance Method, and YuleWalker Method blocks.
The order of the AR model. To guarantee a nonsingular output, the value of this parameter must be less than or equal to half the input length.
When selected, this option specifies that the FFT length is one greater than the estimation order.
Enter the number of data points on which to perform the FFT, N_{fft}. When N_{fft} is larger than the input frame size, the block zeropads each frame as needed. When N_{fft} is smaller than the input frame size, the block wraps each frame as needed. This parameter becomes visible only when you clear the Inherit FFT length from estimation order check box.
When you select the Inherit sample time from input check box, the block computes the frequency data from the sample period of the input signal. For the block to produce valid output, the following conditions must hold:
The input to the block is the original signal, with no samples added or deleted (by insertion of zeros, for example).
The sample period of the timedomain signal in the simulation equals the sample period of the original time series.
If these conditions do not hold, clear the Inherit sample time from input check box. You can then specify a sample time using the Sample time of original time series parameter.
Specify the sample time of the original timedomain signal. This parameter becomes visible only when you clear the Inherit sample time from input check box.
Kay, S. M. Modern Spectral Estimation: Theory and Application. Englewood Cliffs, NJ: PrenticeHall, 1988.
Marple, S. L. Jr., Digital Spectral Analysis with Applications. Englewood Cliffs, NJ: PrenticeHall, 1987.
Orfanidis, S. J. Introduction to Signal Processing. Englewood Cliffs, NJ: PrenticeHall, 1995.
Port  Supported Data Types 

Input 

Output 

Burg Method  DSP System Toolbox 
Covariance AR Estimator  DSP System Toolbox 
Modified Covariance Method  DSP System Toolbox 
ShortTime FFT  DSP System Toolbox 
YuleWalker Method  DSP System Toolbox 
See Spectral Analysis for related information.