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Radar

FMCW Radar with Motion Planning

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This post demonstrates radar platform motion planning using RadarSimPy, showing how to simulate FMCW radar systems mounted on moving platforms (vehicles, drones, robots). You’ll learn to define arbitrary time-varying radar trajectories, understand how platform motion creates Doppler shifts on stationary targets, and analyze Range-Doppler maps for moving radar scenarios. The examples cover linear motion, complex paths, and the critical distinction between radar motion and target motion in relative velocity measurements.

Pulsed Radar

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Pulsed radar transmits short, intense radio pulses to detect and track objects by measuring the time it takes for echoes to return. It’s used in air traffic control, weather monitoring, military surveillance, and navigation. The illustration demonstrates a pulsed radar simulation using the RadarSimPy framework.

Cross-Polarization and Co-Polarization RCS

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In this example, we demonstrate how the RadarSimPy framework can be applied to derive the Cross-Polarization and Co-Polarization RCS of a corner reflector.

DoA Estimation

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RadarSimPy boasts a comprehensive collection of prevalent DoA algorithms and beamformers within its processing module. The following example adeptly showcases the practical application of these algorithms within the realm of a simulated MIMO FMCW radar scenario.

Imaging Radar

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This illustration serves as a prime example of employing ray tracing to simulate the response of a MIMO imaging radar when exposed to a pre-defined 3D scene. This simulation harnesses the robust capabilities of the RadarSimPy framework. Additionally, it provides a fundamental demonstration of the radar signal processing techniques used to generate an image of the scene.

Multi-Path Effect

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In this example, we will employ RadarSimPy’s ray tracing capabilities to demonstrate how vertical multipath effects from the ground can impact the received signal amplitude in an FMCW radar system.

Micro-Doppler

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In this demonstration, we harness the formidable ray tracing capabilities offered by RadarSimPy to simulate the micro-Doppler signature generated by a rotating turbine.

Doppler of a Turbine

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In this demonstration, we leverage the powerful ray tracing capability of RadarSimPy to simulate the intricate Doppler signatures induced by a rotating wind turbine. Additionally, we showcase the step-by-step process of plotting these Doppler signatures on a spectrogram, providing a visual representation of the frequency shifts caused by the turbine’s rotation.

FMCW Radar with a Car

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This illustration exemplifies the utilization of ray tracing to simulate the response of an FMCW radar to a predefined 3D scene, employing the powerful framework of RadarSimPy. Furthermore, it offers a comprehensive demonstration of fundamental range and Doppler processing techniques, enabling the extraction of crucial target information such as range and velocity.

FMCW Radar with a Plate

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This illustration provides a simulation of an FMCW radar system with a rotating metal plate. This simulation is executed through the raytracing framework available in RadarSimPy.