On the optimality of sequential test with multiple sensors

We study the problem of sequential detection for binary hypothesis testing using multiple sensors. We consider a randomized sensor selection strategy in which one sensor can be active at any given time step. We obtain an optimal sequential test using dynamic programming and show that it corresponds to the Sequential Probability Ratio Test (SPRT) when the sensor selection process is stationary. Further, we prove that Wald-Wolfowitz theorem holds true for sequential test with multiple sensors.