레이다

레이다 시스템의 분석, 설계 및 시뮬레이션

MathWorks^® 제품으로 다기능 레이다 시스템을 설계, 시뮬레이션, 분석 및 테스트하여 이러한 시스템의 구현을 위한 출발점으로 활용할 수 있습니다. Radar Toolbox를 다른 제품과 함께 사용하여 물리적 환경에서 움직이고 작동하는 플랫폼인 공중, 지상, 선상, 자동차의 레이다 시스템과 시나리오를 연구합니다.

지정된 요구 사항과 성능 메트릭을 기반으로 레이다 시스템에 상충관계 분석 적용
송신기, 수신기, 전파 채널, 표적, 재머, 클러터를 다양한 추상화 수준에서 모델링
능동 및 수동 위상 배열을 시뮬레이션하여 빔포밍 및 신호 처리 알고리즘 설계
다양한 좌표계와 지도를 사용하여 플랫폼, 궤적, 경로, 환경, 센서를 포함하는 자율 시스템 시나리오를 설계하고 시뮬레이션
레이다 측정값에 다른 실제 센서 및 센서 배열의 데이터를 융합
검출 및 추적 통계량을 컴파일 및 처리하고 다중 객체 추적기와 추정 필터를 사용하여 아키텍처 평가

Deep Learning Toolbox™를 사용하여 사용자의 설계와 모델에 AI를 통합합니다. 이렇게 개발한 신호 처리 알고리즘으로부터 MATLAB^® Coder™를 사용해서 코드를 생성하고 하드웨어에 솔루션을 배포합니다.

레이다 관련 제품

Radar Toolbox

Design, simulate, and test multifunction radar systems

Phased Array System Toolbox

Design and simulate phased array and beamforming systems

Sensor Fusion and Tracking Toolbox

Design, simulate, and test multisensor tracking and positioning systems

Mapping Toolbox

Analyze and visualize geographic information

도움말 항목

모델링 및 시뮬레이션

Airborne SAR System Design (Radar Toolbox)
Design an X-band Synthetic Aperture Radar (SAR) sensor parameters.
Radar Signal Simulation and Processing for Automated Driving (Radar Toolbox)
Model the hardware, signal processing, and propagation environment of an automotive radar.

매핑

Create Maps with Data in Projected Coordinate Reference Systems (Mapping Toolbox)
Create a map using multiple data sets with coordinates in geographic and projected coordinate reference systems.
Export Images and Raster Grids to GeoTIFF (Mapping Toolbox)
Write data referenced to standard geographic and projected coordinate systems to GeoTIFF files.

상황 인식 및 상태 추정

Extended Object Tracking of Highway Vehicles with Radar and Camera (Sensor Fusion and Tracking Toolbox)
Track highway vehicles around an ego vehicle as extended objects that span multiple sensor resolution cells.
Visual-Inertial Odometry Using Synthetic Data (Sensor Fusion and Tracking Toolbox)
Estimate the pose (position and orientation) of a ground vehicle using an inertial measurement unit (IMU) and a monocular camera.

객체 추적 및 모션 계획

Object Tracking and Motion Planning Using Frenet Reference Path (Sensor Fusion and Tracking Toolbox)
Dynamically plan the motion of an autonomous vehicle based on estimates of the surrounding environment.
Adaptive Tracking of Maneuvering Targets with Managed Radar (Radar Toolbox)
This example employs radar resource management to efficiently track multiple maneuvering targets. An interacting multiple model (IMM) filter estimates when the target is maneuvering to optimize radar revisit times.

머신러닝 및 딥러닝

Label Radar Signals with Signal Labeler (Radar Toolbox)
Label the time and frequency features of pulse radar signals with added noise.
Radar and Communications Waveform Classification Using Deep Learning (Phased Array System Toolbox)
Classify radar and communications waveforms using the Wigner-Ville distribution (WVD) and a deep convolutional neural network (CNN).

하드웨어 배포

FPGA-Based Range-Doppler Processing - Algorithm Design and HDL Code Generation (Phased Array System Toolbox)
Design a range-Doppler response that is implementation-ready for a FPGA and compare a simulation output of the model with a Simulink^® behavioral model.
Estimating Orientation Using Inertial Sensor Fusion and MPU-9250 (Sensor Fusion and Tracking Toolbox)
Obtain data from an InvenSense MPU-9250 IMU sensor, and to use the 6-axis and 9-axis fusion algorithms in the sensor data to compute orientation of the device.

추천 예제

Phased Array Gallery

Model and visualize a variety of antenna, microphone, and hydrophone array geometries with Phased Array System Toolbox™.

Radar Link Budget Analysis

Use the Radar Designer app to perform a link budget analysis when designing a radar system. Set the radar performance requirements, compute radar metrics, configure the environment, and compare several alternative designs.

Pedestrian and Bicyclist Classification Using Deep Learning

Classify pedestrians and bicyclists based on their micro-Doppler characteristics using deep learning and time-frequency analysis.

Visualize Aircraft Line-of-Sight over Terrain

Compute and visualize line-of-sight visibility of an aircraft from a ground location over terrain.

Planning Radar Network Coverage over Terrain

Plan a radar network using propagation modelling over terrain. DTED level-1 terrain data is imported for a region that contains five candidate monostatic radar sites. The radar equation is used to determine whether target locations can be detected, where additional path loss is calculated using either the Longley-Rice propagation model or Terrain Integrated Rough Earth Model™ (TIREM™). The best three sites are selected for detection of a target that is flying at 500 meters above ground level. The scenario is updated to model a target that is flying at 250 meters above ground level. Radar coverage maps are shown for both scenarios.

Lidar and Radar Fusion in Urban Air Mobility Scenario

Use multiobject trackers to track various unmanned aerial vehicles in an urban environment.

Processor-in-the-Loop Verification of JPDA Tracker for Automotive Applications

Generate embedded code for a JPDA tracker and verify it using processor-in-the-loop (PIL) simulations.

Assessing Performance with the Tracker Operating Characteristic

Assess the probability of target track and the probability of false track.

레이다