  Detecting the presence of a random wireless source with minimum latency
utilizing an array of radio sensors is considered. The problem is studied under
the constraint that the analog-to-digital conversion at each sensor is
restricted to reading the sign of the analog received signal. We formulate the
resulting digital signal processing task as a sequential hypothesis test in
simple form. To circumvent the intractable probabilistic model of the
multivariate binary array data, a reduced model representation within the
exponential family in conjunction with a log-likelihood ratio approximation is
employed. This approach allows us to design a likelihood-based sequential test
and to analyze its analytic performance along Wald's classical arguments. In
the context of wireless spectrum monitoring for satellite-based navigation and
synchronization systems, we study the achievable processing latency,
characterized by the average sample number, as a function of the binary sensors
in use. The practical feasibility and potential of the discussed low-complexity
sensing and decision-making technology is demonstrated via simulations.
