# LCMV Beamformer

Narrowband linear constraint minimum variance (LCMV) beamformer

**Libraries:**

Phased Array System Toolbox /
Beamforming

## Description

The LCMV Beamformer block performs narrowband linear-constraint minimum-variance (LCMV) beamforming. The number of constraints must be less than the number of elements or subarrays in the array.

## Ports

### Input

**X** — Input signal

*M*-by-*N* complex-valued
matrix

Input signals to beamformer, specified as an *M*-by-*N* complex-valued
matrix. *M* is the number of signal samples. *N* is
the number of sensor array elements.

The size of the first dimension of the input matrix can vary to simulate a changing signal length. A size change can occur, for example, in the case of a pulse waveform with variable pulse repetition frequency.

**Data Types: **`double`

**Complex Number Support: **Yes

**XT** — Training signal

*P*-by-*N* complex-valued
matrix

Training input signal, specified as a *P*-by-*N* complex-valued
matrix. *P* is the number of samples in the training
input signal. *N* is the number of elements of the
sensor array. *P* must be greater than *N*.

The size of the first dimension of the input matrix can vary to simulate a changing signal length. A size change can occur, for example, in the case of a pulse waveform with variable pulse repetition frequency.

#### Dependencies

To enable this port, select the **Enable training data
input** checkbox.

**Data Types: **`double`

**Complex Number Support: **Yes

### Output

**Y** — Beamformed output

*M*-by-1 complex-valued column vector

Beamformed output, specified as an *M*-by-1
complex-valued column vector. *M* is the number of
signal samples.

**Data Types: **`double`

**Complex Number Support: **Yes

**W** — Beamformer weights output

*N*-by-1 complex-valued column vector

Beamformer weights output, specified as an *N*-by-1
complex-valued column vector. *N* is the number of
array elements.

#### Dependencies

To enable this port, select the **Enable weights output** checkbox.

**Data Types: **`double`

**Complex Number Support: **Yes

## Parameters

**Constraint matrix** — LCMV beamformer constraint matrix

`complex([1;1])`

(default) | *N*-by-*K* complex-valued
matrix

LCMV beamformer constraint matrix specified as an *N*-by-*K* complex-valued
matrix. Each column of the matrix is a constraint. *N* is
the number of elements in the sensor array and *K* is
the number of constraints. *K* must be less than
or equal to the number of sensors, *N*,*K
≤ N*

**Desired response vector** — Desired response for LCMV beamforming

`1`

(default) | real-valued *K*-by-1 column vector

Desired response of the LCMV beamformer, specified as a real-valued *K*-by-1
column vector. *K* is the number of constraints in
the **Constraint matrix**. Each element in the vector
defines the desired response of the constraint specified in the corresponding
column of the **Constraint matrix** parameter.

**Diagonal loading factor** — Diagonal loading factor

positive scalar

Diagonal loading factor, specified as a positive scalar. Diagonal loading is a technique used to achieve robust beamforming performance, especially when the sample support is small.

**Enable training data input** — Enable training data input port

`off`

(default) | `on`

Enable training data input port, specified as `off`

or `on`

.
To enable the training data input port, `XT`

, select
this checkbox.

**Enable weights output** — Enable output of beamformer weights

`off`

(default) | `on`

Enable beamforming weights output port, specified as `off`

or `on`

.
To enable the beamforming weights output port, `W`

,
select this checkbox.

**Simulate using** — Block simulation method

`Interpreted Execution`

(default) | `Code Generation`

Block simulation, specified as `Interpreted Execution`

or
`Code Generation`

. If you want your block to use the
MATLAB^{®} interpreter, choose `Interpreted Execution`

. If
you want your block to run as compiled code, choose ```
Code
Generation
```

. Compiled code requires time to compile but usually runs
faster.

Interpreted execution is useful when you are developing and tuning a model. The block
runs the underlying System object™ in MATLAB. You can change and execute your model quickly. When you are satisfied
with your results, you can then run the block using ```
Code
Generation
```

. Long simulations run faster with generated code than in
interpreted execution. You can run repeated executions without recompiling, but if you
change any block parameters, then the block automatically recompiles before
execution.

This table shows how the **Simulate using** parameter affects the
overall simulation behavior.

When the Simulink^{®} model is in `Accelerator`

mode, the block mode specified
using **Simulate using** overrides the simulation mode.

**Acceleration Modes**

Block Simulation | Simulation Behavior | ||

`Normal` | `Accelerator` | `Rapid Accelerator` | |

`Interpreted Execution` | The block executes using the MATLAB interpreter. | The block executes using the MATLAB interpreter. | Creates a standalone executable from the model. |

`Code Generation` | The block is compiled. | All blocks in the model are compiled. |

For more information, see Choosing a Simulation Mode (Simulink).

#### Programmatic Use

Block
Parameter:`SimulateUsing` |

Type:enum |

Values:```
Interpreted
Execution
``` , `Code Generation` |

Default:```
Interpreted
Execution
``` |

## Version History

**Introduced in R2014b**

## See Also

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