Abstract: In a multiple signal wireless communication system, it is important to be able to effectively separate signals. This separation has traditionally been accomplished in the frequency and time domains. High resolution spatial signal separation can also be accomplished with a small number of antennas by following the proper mathematical method. This involves modeling multiple communication signals that map onto an antenna array in the receive case and by modeling the multiple antenna output signals that form multiple transmit signals. Inverting these processes by use of the Moore-Penrose inverse results in complete spatial separation of the signals of interest. This novel method has important applications in wireless communication systems.

Abstract: In a multiple signal environment, it is important to be able to separate signals. Complete spatial separation can only be accomplished by following the proper mathematical method. This involves first modeling multiple signals that map onto an antenna array. Inverting this process by use of the Moore-Penrose inverse results in spatially separating the signals of interest. This method has important applications in satellite navigation systems where it is relatively easy to jam or spoof the valid but weak navigation signals coming from satellites in high orbits.

Abstract: In a multiple signal environment, it is important to be able to separate signals. Complete spatial separation can only be accomplished by following the proper mathematical method. This involves first modeling multiple signals that map onto an antenna array. Inverting this process by use of the Moore-Penrose inverse results in spatially separating the signals of interest. This method has important applications in satellite navigation systems where it is relatively easy to jam or spoof the valid but weak navigation signals coming from satellites in high orbits.