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Detection

Target detection, CFAR, CFAR 2D, ROC curves, radar equation

The Phased Array System Toolbox™ includes System objects and Simulink® blocks for performing matched filtering, constant false alarm rate (CFAR) detection in one or two dimensions, stretch-processing pulse compression and coherent and noncoherent pulse integration. Utility functions let you compute and visualize receiver operating characteristic (ROC) curves for various signal-to-noise ratio (SNR) levels or probabilities of false alarm. Some utilities let determine the maximum target detection range. Others let you visualize radar coverage using Blake charts.

System Objects

phased.CFARDetector Constant false alarm rate (CFAR) detector
phased.CFARDetector2D Two-dimensional CFAR detector
phased.MatchedFilter Matched filter
phased.StretchProcessor Stretch processor for linear FM waveform
phased.TimeVaryingGain Time varying gain control

Blocks

CFAR Detector Constant false alarm rate (CFAR) detector
2-D CFAR Detector Two-dimensional constant false alarm rate (CFAR) detector
Stretch Processor Stretch processor for linear FM waveforms
Time Varying Gain Time varying gain (TVG) control
Pulse Integrator Coherent or noncoherent pulse integration
Dechirp Mixer Dechirping operation on input signal
Matched Filter Matched filter

Functions

albersheim Required SNR using Albersheim's equation
dechirp Perform dechirp operation on FMCW signal
npwgnthresh Detection SNR threshold for signal in white Gaussian noise
pulsint Pulse integration
rocpfa Receiver operating characteristic curves by false-alarm probability
rocsnr Receiver operating characteristic curves by SNR
shnidman Required SNR using Shnidman's equation
blakechart Range-angle-height (Blake) chart
physconst Physical constants
radareqpow Peak power estimate from radar equation
radareqrng Maximum theoretical range estimate
radareqsnr SNR estimate from radar equation
radarvcd Vertical coverage diagram

Apps

Radar Equation Calculator Estimate maximum range, peak power, and SNR of a radar system

Topics

Detection and Estimation Examples

Neyman-Pearson Hypothesis Testing

In phased-array applications, you sometimes need to decide between two competing hypotheses to determine the reality underlying the data the array receives.

Receiver Operating Characteristics

Receiver operating characteristic (ROC) curves describe a detector's performance by relating probability of false alarm to probability of detection.

Monte-Carlo ROC Simulation

This example shows how to generate a receiver operating characteristic (ROC) curve of a radar system using a Monte-Carlo simulation.

Matched Filtering

Matched filtering increases SNR and improves detection.

Stretch Processing

Stretch processing, deramp, dechirp

FMCW Range Estimation

FMCW dechirp

Range-Doppler Response

Range-Doppler processing and range-Doppler maps

Constant False-Alarm Rate (CFAR) Detectors

CFAR detectors apply the Neyman-Pearson criterion to target detection. The detectors estimate noise statistics from data.

Phased Array System Examples

Overview of Basic Workflow

This section provides an introduction to the end-to-end radar simulation.

End-to-End Radar System

The basic toolbox workflow is applied to a monostatic radar system consisting of a single antenna.

Concepts

Radar Equation

Radar equation for peak power, range, and SNR in monostatic and bistatic configurations

Standards and Conventions

This section introduces the concept of baseband signals and defines the local and global coordinate systems used in the toolbox.

Units of Measure and Physical Constants

Phased Array System Toolbox uses the International System of Units.

What Are System Objects?

Defines System objects and key uses

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