Range Estimator
Range estimation
Libraries:
Phased Array System Toolbox /
Detection
Description
The Range Estimator block estimates the range of target detections obtained from the radar response data.
Ports
Input
Resp — Range-processed response data cube
complex-valued P-by-1 column vector | complex-valued M-by-P matrix | complex-valued M-by-N-by-P matrix
Range-processed response data cube, specified as a complex-valued P-by-1 column vector, a complex-valued M-by-P matrix, or a complex-valued M-by-N-by-P array. M represents the number of range samples, N is the number of sensor elements or beams, and P is the number of Doppler bins.
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
Range — Range grid values along range dimension
real-valued M-by-1 column vector
Range grid values along the range dimension of the data cube input, Resp, specified as a real-valued M-by-1 column vector. Range values must be monotonically increasing and equally spaced. Units are in meters.
Example: [-0.3,-0.2,-0.1,0,0.1,0.2,0.3]
Data Types: double
DetIdx — Detection indices
real-valued Nd-by-Q matrix
Detection indices, specified as a real-valued Nd-by-Q matrix. Q is the number of detections and Nd is the number of dimensions in the response data cube, Resp. Each column of DetIdx contains the indices of a detection in the response data cube.
NoisePower — Noise power at detection locations
positive scalar | real-valued 1-by-Q row vector of positive
values
Noise power at detection locations, specified as a positive scalar or real-valued 1-by-Q row vector positive values. Q is the number of detections specified in the DetIdx input port.
Dependencies
To enable this port, select the Output variance for
parameter estimates parameter, and then set Source
of noise power parameter to Input port
.
Clusters — Cluster IDs
real-valued 1-by-Q row vector of positive
values
Cluster IDs, specified as a real-valued 1-by-Q row vector, where Q is the number of detections specified in the DetIdx input port. Each element of Clusters corresponds to an element of DetIdx.
Dependencies
To enable this input port, select the Enable cluster ID input checkbox.
Output
Est — Range estimate
real-valued K-by-1 column vector
Range estimates, specified as a real-valued K-by-1 column vector.
When Enable cluster ID input is not selected, each range estimate corresponds to one of the columns of the DetIdx input port. Then K equals the column dimension, Q, of DetIdx.
When Enable cluster ID input is selected, each range estimate corresponds to one of the cluster IDs in the Clusters input port. Then K equals the number of unique cluster IDs.
Var — Range estimation variance
positive, real-valued K-by-1 column vector
Range estimation variance, returned as a positive, real-valued K-by-1 column vector, where K is the dimension of Est. Each element of Var corresponds to an element of Est. The estimator variance is computed using the Ziv-Zakai bound.
Dependencies
To enable this output port, select the Output variance for parameter estimates parameter.
Parameters
Maximum number of estimates — Maximum number of estimates to report
1
(default) | positive integer
The maximum number of estimates to report, specified as a positive
integer. When the number of requested estimates is greater than the
number elements in DetIdx, the remainder is filled
with NaN
.
Data Types: double
Enable cluster ID input — Enable cluster ID input
off
(default) | on
Enable the Cluster input port to pass in cluster association information.
Data Types: Boolean
Output variance for parameter estimates — Enable output variance port
off
(default) | on
Enables the output of the parameter estimate variances via the Var port.
Data Types: Boolean
Root-mean-square range resolution — Range resolution
2
(default) | positive scalar
Root-mean-square range resolution of the detection, specified as a positive scalar. This parameter must have the same units as the Range input port.
Dependencies
To enable this parameter, select the Output variance
for parameter estimates
parameter.
Data Types: double
Source of noise power — Source of noise power values
Property
(default) | Input port
Source of the noise power, specified as Property
or Input
port
. If you set this parameter to Property
,
use the Noise power parameter to set the noise
power at the detection locations. When set the parameter to Input
port
, specify noise power via the NoisePower
input
port.
Noise power — Noise power values
1.0
(default) | positive scalar
Noise power for detections, specified as a positive scalar. The same noise power value is applied to all detections. Noise power is in linear units.
Dependencies
To enable this parameter, select the Output variance
for parameter estimates checkbox and set the Source
of noise power parameter to Property
.
Data Types: double
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 R2017a
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