High-Performance Passive Eigen-Model-Based Detectors of Single Emitter Using Massive MIMO Receivers

For a passive direction of arrival (DOA) measurement system using massive multiple input multiple output (MIMO), it is mandatory to infer whether the emitter exists or not before performing DOA estimation operation. Inspired by the detection idea from radio detection and ranging (radar), three high-performance detectors are proposed to infer the existence of single or multiple passive emitter from the eigen-space of sample covariance matrix of receive signal vector. The first test statistic (TS) is defined as the ratio of maximum eigen-value (Max-EV) to minimum eigen-value (R-MaxEV-MinEV) while the second one is defined as the ratio of Max-EV to noise variance (R-MaxEV-NV). The third TS is the mean of maximum eigen-value (EV) and minimum EV(M-MaxEV-MinEV). Their closed-form expressions are presented and the corresponding detection performance is given. Simulation results show that the proposed M-MaxEV-MinEV and R-MaxEV-NV methods can approximately achieve the same detection performance better than the traditional generalized likelihood ratio test method and energy detection method with a given false alarm probability.