MIMO Radar Clutter Modeling

ABSTRACT: Radars have long been an important sensor used on the battlefield for detecting and tracking adversary movements as well as for imaging and target identification. One of the primary factors that determines the performance of a radar is the signal processing algorithms used to detect targets in clutter. State-of-the art radars use advanced adaptive signal processing techniques to achieve a high degree of clutter cancellation which allows for weak targets such as vehicles and dismounts to be reliably detected and tracked. Reliable performance evaluation of adaptive signal processing algorithms requires a detailed characterization of the clutter which is highly dependent on the specific operating environment (buildings, terrain, trees, etc.) as well as the various electromagnetic propagation and scattering mechanisms that influence the received clutter signals. ISL is pleased to propose an STTR program that will develop a physics-based radar simulation and modeling tool that takes as input 3D models of any radar operating environment and is capable of providing multi-dimensional radar data outputs with realistic statistical and spectral properties that can be used to evaluate algorithm performance of MIMO radars. BENEFIT: The developed tools will provide the research community including universities, DoD laboratories and prime contractors developing next generation MIMO radars with simulation tools that can be used to accurately predict real-world system performance without the need for expensive and time-consuming field experiments. Additionally, the new simulation tools have the potential for application to other RF sensor disciplines including wireless communications, signals intercept and intelligences and navigation.