  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
passive emitter from the eigen-space of sample covariance matrix of receive
signal vector. The test statistic (TS) of the first method is defined as the
ratio of maximum eigen-value (Max-EV) to minimum eigen-value (R-MaxEV-MinEV)
while that of the second one is defined as the ratio of Max-EV to noise
variance (R-MaxEV-NV). The TS of the third method 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 that is better than the
traditional generalized likelihood ratio test method with false alarm
probability being less than 0.3.
