Phased Array System Toolbox
Design and simulate phased array signal processing systems
Phased Array System Toolbox™ provides algorithms and apps for the design, simulation, and analysis of sensor array systems in radar, wireless communication, EW, sonar, and medical imaging applications. You can design phased array systems and analyze their performance under different scenarios using synthetic or acquired data. Toolbox apps let you explore the characteristics of sensor arrays and waveforms and perform link budget analysis. In-product examples provide a starting point for implementing a full range of phased array multifunction systems that require frequency, PRF, waveform, and beam pattern agility.
For radar sonar, and EW system design, the toolbox lets you model dynamics and targets for ground-based, airborne, ship-borne, submarine, and automotive systems. It includes pulsed and continuous waveforms and signal processing algorithms for beamforming, matched filtering, direction of arrival (DOA) estimation, and target detection. The toolbox also includes models for transmitters and receivers, propagation channels, targets, jammers, and clutter.
For 5G, LTE, and WLAN wireless communications system design, the toolbox enables you to incorporate antenna arrays and beamforming algorithms into system-level simulation models. It includes capabilities for designing and analyzing array geometries and subarray configurations, and provides array processing algorithms for conventional and hybrid beamforming, DOA estimation, and spatial multiplexing.
Phased Array Design
Model and analyze the behavior of active or passive electronically scanned arrays (AESA or PESA) with arbitrary geometries.
Design and Analyze Phased Arrays
Model and analyze phased arrays, including the array geometry, element spacing, custom antenna elements, phased shift quantization, mutual coupling, and perturbed elements.
Phased array gallery.
Subarray Modeling
Model subarrays commonly used in modern phased array systems.
Subarrays in phased array antennas.
Polarization
Transmit, propagate, reflect, and receive polarized electromagnetic fields.
Modeling and analyzing polarization.
Beamforming and DOA Estimation
Model narrowband and broadband digital beamforming algorithms. Suppress interferences and avoid self-nulling with adaptive beamformers. Use space-time adaptive processing (STAP) techniques to remove clutter and jammer. Estimate direction of arrival (DOA) of incident signals.
Narrowband and Broadband Beamforming
Model narrowband and wideband digital beamforming algorithms. The algorithms cover spectral-based and covariance-based techniques.
Conventional and adaptive beamformers.
Space-Time Adaptive Processing
Perform space-time adaptive processing (STAP). Combine temporal and spatial filtering to nullify interfering jammers. Use STAP processing to detect slow-moving or stationary targets in background clutter.
Introduction to space-time adaptive processing.
Direction of Arrival Estimation
Use direction of arrival (DOA) estimation to localize the direction of a radiating or reflecting source. DOA algorithms include beamscan, MVDR, MUSIC, 2D MUSIC, root-MUSIC, and monopulse trackers for moving objects.
DOA estimation with beamscan, MVDR, and MUSIC.
Complex Signal Data Generation
Generate radar, sonar, and EW data for performance analysis and to train machine learning algorithms.
IQ Data Generation
Generate IQ data for radar, sonar, and EW for performance analysis.
Radar echo simulation.
Train Learning Algorithms
Generate radar and sonar data to train machine learning algorithms.
Radar target classification using machine learning.
Waveform Design and Analysis
Define waveforms and waveform libraries. You can analyze spectral properties, range resolution, and Doppler resolution.
Pulse and Continuous Waveforms
Design pulse and continuous waveforms and generate baseband IQ data.
Waveform analysis using the ambiguity function.
PRF and Frequency-Agile Waveforms
Create pulse waveform libraries with PRF and frequency agility.
Waveform agility.
Detection Visualization
Visualize data using range-Doppler, range-angle, range-time-intensity (RTI), and Doppler-time-intensity (DTI) displays.
Range-angle display.
Detection, Range, and Doppler Estimation
Perform matched filtering, stretch processing, pulse compression, pulse integration, range and Doppler estimation, and CFAR detection.
Pulse Compression and Target Detection
Generate target detections using CFAR, 2D CFAR, and matched filters. Generate ROC curves and explore requirements using radar equation and sonar equation.
Constant false alarm rate detection.
Range and Doppler Estimation
Estimate range, range-Doppler processing, range-angle, and FMCW range estimation.
Range-Doppler response.
Target, Interference, and Channel Model
Define complex scenarios, including distributed target models with complex trajectories. You can also model a range of propagation channels, clutter, and jammer interferences.
Model Targets and Target Trajectories
Model targets with RCS patterns based on azimuth, elevation, and frequency. Define sensor and target trajectories.
Model target RCS.
Multipath MIMO Channels
Model multipath MIMO channels with scatterers and environmental conditions, including rain, gas, and fog.
Visual array beam scanning.
Interference and Clutter
Generate interference sources and clutter models.
Ground clutter with an MTI radar.
Application Examples
Simulate radar, sonar, EW systems, automotive, and MIMO communication systems.
Radar, Sonar, and EW
Simulate radar, sonar, and EW systems.
Resource scheduling for multifunction radar.
MIMO Communication Systems
Model MIMO communication systems.
Introduction to hybrid beamforming.
Automotive Radar
Simulate automotive radar systems at the IQ signal level.
Modeling a radar system for a driving scenario.
Algorithm Acceleration
Speed up simulations and applications with generated C/C++ and MEX code, or by using GPUs or Dataflow.
Accelerate Clutter Simulation
Accelerate clutter simulations using a GPU or code generation (MEX).
Acceleration of clutter simulation using GPU and code generation.
C Code Generation
Generate C code for the model to accelerate system simulation.
Stream and accelerate simulation of a radar system.
Dataflow to Accelerate Simulation
Use Dataflow to accelerate simulation times by using parallel processing threads.
Data flow acceleration.
Latest Features
Bicyclist Radar Backscatter Model
Simulate backscattered radar signals from a bicycle and rider
Detection Clustering
Cluster radar detections using density-based spatial clustering of applications with noise (DBSCAN) algorithm
Hybrid Beamforming
Compute optimum weights for MIMO beamforming based on orthogonal matching pursuit algorithms
Sensor Array Analyzer
Design and analyze phased arrays for radar, wireless, and sonar applications
Terrain Integrated Rough Earth Model (TIREM) Path Loss
Compute RF propagation loss using TIREM
See the release notes for details on any of these features and corresponding functions.
