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.
RadarSimM v3.0 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.
RadarSimPy v12.3.x 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. This release brings improvements in performance, user interface, and functionality.
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.
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.