Note: This page has been translated by MathWorks. Please click here

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Spatial smoothing

`RSM = spsmooth(R,L)`

`RSM = spsmooth(R,L,'fb')`

computes
an averaged spatial covariance matrix, `RSM`

= spsmooth(`R`

,`L`

)`RSM`

, from
the full spatial covariance matrix, `R`

, using *spatial
smoothing* (see Van Trees [1], p. 605). Spatial smoothing
creates a smaller averaged covariance matrix over *L* maximum
overlapped subarrays. *L* is a positive integer less
than *N*. The resulting covariance matrix, `RSM`

,
has dimensions (*N*–*L*+1)-by-(*N*–*L*+1).
Spatial smoothing is useful when two or more signals are correlated.

[1] Van Trees, H.L. *Optimum Array
Processing*. New York, NY: Wiley-Interscience, 2002.

`aictest`

| `espritdoa`

| `mdltest`

| `rootmusicdoa`

Was this topic helpful?