RadarSimM v2.0 is the latest version of our radar simulation software, packed with new features, enhancements, and optimizations to provide you with an even better radar simulation experience.
Consider utilizing RadarSimPy for a simulation example involving interferometric radar. This simulation employs RadarSimPy to capture subtle movements of an ideal point target, showcasing the radar’s measurement capabilities.
In this illustrative example, we will showcase the process of configuring an interference radar within the simulation environment. Subsequently, we will delve into the exploration of its consequential impact on the baseband samples of a victim radar.
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.
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.
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.
In this demonstration, we harness the formidable ray tracing capabilities offered by RadarSimPy to simulate the micro-Doppler signature generated by a rotating turbine.
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.
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.
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.