Main Content

Target detection, target tracking, CFAR, 2-D CFAR, ROC curves, radar
equation, sonar 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. A suite of functions and an app
let you perform radar analysis using the radar equation. You can
estimate, for example, received SNR or maximum target detection range. A
similar set of capabilities are provided for the sonar equation. Blake
charts let you visualize radar coverage.

`AlphaBetaFilter` | Alpha-beta filter for object tracking |

`phased.CFARDetector` | Constant false alarm rate (CFAR) detector |

`phased.CFARDetector2D` | Two-dimensional CFAR detector |

`phased.MatchedFilter` | Matched filter |

`phased.PulseCompressionLibrary` | Create a library of pulse compression specifications |

`phased.StretchProcessor` | Stretch processor for linear FM waveform |

`phased.TimeVaryingGain` | Time varying gain control |

CFAR Detector | Constant false alarm rate (CFAR) detector |

2-D CFAR Detector | Two-dimensional constant false alarm rate (CFAR) detector |

Pulse Compression Library | Library of pulse compression specifications |

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 |

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

Sonar Equation Calculator | Estimate maximum range, SNR, transmission loss and source level of a sonar system |

Sensor Array Analyzer | Analyze beam patterns and performance characteristics of linear, planar, 3-D, and arbitrary sensor arrays |

**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.

Generate an ROC curve using a Monte-Carlo simulation.

Matched filtering increases SNR and improves detection.

Stretch processing, also known as deramping or dechirping, is an alternative to matched filtering.

FMCW range estimation dechirps the received signal, extracts beat frequencies, and computes the target range.

Perform range-Doppler processing and visualize 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.

Solve the radar equation for peak power, range, and SNR in monostatic and bistatic configurations.

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 (SI).

The sonar equation is used in underwater signal processing to relate received signal power to transmitted signal power for one-way or two-way sound propagation.

The Doppler effect is the change in the observed frequency of a source due to the motion of either the source or receiver or both.