# Modified Covariance Method

Power spectral density estimate using modified covariance method

Libraries:
DSP System Toolbox / Estimation / Power Spectrum Estimation

## Description

The Modified Covariance Method block estimates the power spectral density (PSD) of the input using the modified covariance method. This method fits an autoregressive (AR) model to the signal by minimizing the forward and backward prediction errors in the least squares sense.

The block computes the spectrum from the FFT of the estimated AR model parameters.

## Ports

### Input

expand all

Specify the input as a column vector or an unoriented vector. This input represents a frame of consecutive time samples from a single-channel signal.

Data Types: `single` | `double`

### Output

expand all

Power spectral density estimate of the signal at Nfft equally spaced frequency points, returned as a column vector. The frequency points are in the range [0,Fs), where Fs is the sampling rate of the signal.

Data Types: `single` | `double`

## Parameters

expand all

Specify the estimation order of the AR model (all-pole model) as a positive integer. The block computes the spectrum from the FFT of the estimated AR model parameters. To guarantee a nonsingular output, the value of the Estimation order parameter must be less than or equal to 2/3 of the input vector length.

When you select the Inherit FFT length from estimation order parameter, the FFT length Nfft is one greater than the estimation order. To specify the number of points on which to perform the FFT, clear the Inherit FFT length from estimation order parameter. You can then specify a power-of-two FFT length using the FFT length parameter. The block zero-pads or wraps the input to Nfft before computing the FFT.

Enter the number of data points Nfft on which to perform the FFT as a positive integer greater than or equal to 2. When Nfft is larger than the input frame size, the block zero-pads each frame as needed. When Nfft is smaller than the input frame size, the block wraps each frame as needed.

#### Dependencies

To enable this parameter, clear the Inherit FFT length from estimation order parameter.

When you select the Inherit sample time from input parameter, 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 time-domain 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 time-domain signal as a positive scalar.

#### Dependencies

To enable this parameter, clear the Inherit sample time from input parameter.

## Block Characteristics

 Data Types `double` | `single` Multidimensional Signals `No` Variable-Size Signals `No`

expand all

## References

[1] Kay, S. M. Modern Spectral Estimation: Theory and Application. Englewood Cliffs, NJ: Prentice-Hall, 1988.

[2] Marple, S. L. Jr., Digital Spectral Analysis with Applications. Englewood Cliffs, NJ: Prentice-Hall, 1987.

[3] Orfanidis, S. J. Introduction to Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1995.

## Version History

Introduced before R2006a