Positions of the elements of a sensor array specified as a 1-by-*N* vector,
a 2-by-*N* matrix, or a 3-by-*N* matrix.
In this vector or matrix, *N* represents the number
of elements of the array. Each column of `pos`

represents
the coordinates of an element. You define sensor position units in
term of signal wavelength. If `pos`

is a 1-by-*N* vector,
then it represents the *y*-coordinate of the sensor
elements of a line array. The *x* and *z*-coordinates
are assumed to be zero. If `pos`

is a 2-by-*N* matrix,
then it represents the *(y,z)*-coordinates of the
sensor elements of a planar array which is assumed to lie in the *yz*-plane.
The *x*-coordinates are assumed to be zero. If `pos`

is
a 3-by-*N* matrix, then the array has arbitrary shape.

**Example: **[0, 0, 0; .1, .2, .3; 0,0,0]

**Data Types: **`double`

Arrival directions of incoming signals specified as a 1-by-*M* vector
or a 2-by-*M* matrix, where *M* is
the number of incoming signals. If `ang`

is a 2-by-*M* matrix,
each column specifies the direction in azimuth and elevation of the
incoming signal `[az;el]`

. Angular units are specified
in degrees. The azimuth angle must lie between –180° and
180° and the elevation angle must lie between –90°
and 90°. The azimuth angle is the angle between the *x*-axis
and the projection of the arrival direction vector onto the *xy* plane.
It is positive when measured from the *x*-axis toward
the *y*-axis. The elevation angle is the angle between
the arrival direction vector and *xy*-plane. It is
positive when measured towards the *z* axis. If `ang`

is
a 1-by-*M* vector, then it represents a set of azimuth
angles with the elevation angles assumed to be zero.

**Example: **[45;0]

**Data Types: **`double`

Noise spatial covariance matrix specified as a non-negative,
real-valued scalar, a non-negative, 1-by-*N* real-valued
vector or an *N*-by-*N*, positive
definite, complex-valued matrix. In this argument, *N* is
the number of sensor elements. Using a non-negative scalar results
in a noise spatial covariance matrix that has identical white noise
power values (in watts) along its diagonal and has off-diagonal values
of zero. Using a non-negative real-valued vector results in a noise
spatial covariance that has diagonal values corresponding to the entries
in `ncov`

and has off-diagonal entries of zero.
The diagonal entries represent the independent white noise power values
(in watts) in each sensor. If `ncov`

is *N*-by-*N* matrix,
this value represents the full noise spatial covariance matrix between
all sensor elements.

**Example: **[1,1,4,6]

**Data Types: **`double`

**Complex Number Support: **Yes

Signal covariance matrix specified as a non-negative, real-valued
scalar, a *1*-by-*M* non-negative,
real-valued vector or an *M*-by-*M* positive
semidefinite, matrix representing the covariance matrix between *M* signals.
The number of signals is specified in `ang`

. If `scov`

is
a nonnegative scalar, it assigns the same power (in watts) to all
incoming signals which are assumed to be uncorrelated. If `scov`

is
a 1-by-*M* vector, it assigns the separate power
values (in watts) to each incoming signal which are also assumed to
be uncorrelated. If `scov`

is an *M*-by-*M* matrix,
then it represents the full covariance matrix between all incoming
signals.

**Example: **[1 0 ; 0 2]

**Data Types: **`double`

**Complex Number Support: **Yes