Abstract: A novel and useful two-stage radar return data processing mechanism for use in FMCW radar systems that divides the conventional frame into two portions. Two different frames are transmitted rather than one. The frames are transmitted consecutively one after the other. A low resolution ‘coarse’ frame is first transmitted that is fully processed in real time. Based on the results of the processing of the coarse frame, a plurality of targets of interest (TOIs) in the scene representing a subset of the received data is determined. Then a longer high-resolution ‘fine’ frame is transmitted and processed using the information obtained in the previous coarse fame. Using the TOI information obtained in the previous coarse frame, only a subset of the received data is processed. The non-processed portion is assumed to contain non-interesting information and is discarded or ignored thereby significantly reducing processing time.

Abstract: A novel and useful two-stage radar return data processing mechanism for use in FMCW radar systems that divides the conventional frame into two portions. Two different frames are transmitted rather than one. The frames are transmitted consecutively one after the other. A low resolution ‘coarse’ frame is first transmitted that is fully processed in real time. Based on the results of the processing of the coarse frame, a plurality of targets of interest (TOIs) in the scene representing a subset of the received data is determined. Then a longer high-resolution ‘fine’ frame is transmitted and processed using the information obtained in the previous coarse fame. Using the TOI information obtained in the previous coarse frame, only a subset of the received data is processed. The non-processed portion is assumed to contain non-interesting information and is discarded or ignored thereby significantly reducing processing time.

Abstract: A method for performing Simultaneous Localization And Mapping (SLAM) of the surroundings of an autonomously controlled moving platform (such as UAV or a vehicle), using radar signals, comprising the following steps: receiving samples of the received IF radar signals, from the DSP; receiving previous map from memory; receiving data regarding motions parameters of the moving platform from an Inertial Navigation System (INS) module, containing MEMS sensors data; grouping points to bodies using a clustering process; merging bodies that are marked by the clustering process as separate bodies, using prior knowledge; for each body, creating a local grid map around the body with a mass function per entry of the grid map; matching between bodies from previous map and the new bodies; calculating the assumed new location of the moving platform for each on the mL particles using previous frame results and new INS data; for each calculated new location of the mL particles with normal distribution, sampling N assumed locat

Abstract: A method for performing Simultaneous Localization And Mapping (SLAM) of the surroundings of an autonomously controlled moving platform (such as UAV or a vehicle), using radar signals, comprising the following steps: receiving samples of the received IF radar signals, from the DSP; receiving previous map from memory; receiving data regarding motions parameters of the moving platform from an Inertial Navigation System (INS) module, containing MEMS sensors data; grouping points to bodies using a clustering process; merging bodies that are marked by the clustering process as separate bodies, using prior knowledge; for each body, creating a local grid map around the body with a mass function per entry of the grid map; matching between bodies from previous map and the new bodies; calculating the assumed new location of the moving platform for each on the mL particles using previous frame results and new INS data; for each calculated new location of the mL particles with normal distribution, sampling N assumed locat