Key to On-Orbit Approach is a robust system having accuracy of range, velocity, and direction of travel, while minimizing size, weight, and power (SWaP). The system performing and capturing this information will likely be a set of complementary sensors including radars. Current radars are susceptible to the risk of jamming and interference, especially in highly electromagnetically congested or uncertain environments. The space environment might be uncertain or potentially electromagnetically congested. This proposal is to provide Space Force a low SWaP, robust system that can effectively perform in the harsh environment of space using a multimodal noise-based radar with antenna beamforming. This proposal is to evolve RF Noise radars with enhanced features, named antenna beamforming and artificial intelligence. Firstly, antenna beamforming allows to selectively steer or adjust the antenna beam over the potential antenna field of view, instead of having a single antenna pattern over the antenna field of view. This allows the antenna system to have the operational capability of multiple antennas using only one antenna, resulting in a reduction of size and weight. In addition, the use of a single antenna flexibilizes the design of the launch and deployment form factors of the spacecraft carrying the radar. Further, antenna beamforming allows the radar to operate in multiple modes, according to the environmental situation and range to targets of interest. In this sense, at long ranges, the radar might be set up in a search and surveillance mode, with the broadest antenna pattern, to determine the general location of an object of interest. At middle ranges, the radar might be set up in a tracking mode, having a narrower antenna beam, with a reduced transmitted power, while providing a more accurate location of the object to be approached. At short ranges, the radar might be in an approaching mode, with the narrowest antenna beam, and further reduce the transmitted power, while increasing the accuracy of the object of interest location. The specific ranges and modes of operation of the radar might be determined based on the specific environmental situation, customer input, and the complementary sensors onboard as part of the On-Orbit Approach overall solution. Moreover, the multimodal feature of the proposed radar might be helpful as a backup in case of failure of other approaching sensors. The second feature is the implementation of Artificial Intelligence. Specifically, customized machine learning algorithms may be developed to identify targets of interest, efficiently power-manage the radar system, and/or support the decision making as to when to switch the radar operating mode.
