Active Detection With a Barrier Sensor Network Using a Scan Statistic

Abstract-The cooperation of an active acoustic source and a large number of distributed passive sensors offers an opportunity for active sonar detection. The system works as follows: first, each sensor compares its matched filter output with a given threshold to obtain a binary local decision-"0" or "1"; then, a fusion center (FC) collects them to make a system-level inference. How effectively to combine these local results-distributed detection fusion-is the concentration of this paper. Suppose that the sensor network is unaware of the target\´s reflection model. Then, the local detection probabilities cannot be obtained; therefore, the optimal fusion rule is unavailable. The obvious detection strategy is a counting rule test (CRT), which simply counts the total number of 1\´s and compares it to a threshold. This approach does not require knowledge of sensor locations, and equally considers all network subareas. However, the reflected signal from some targets, such as a submarine, can be highly aspect dependent, and in many instances only sensors in a particular zone can receive its echoes. This paper focuses on the scan statistic, which slides a window across the sensor field, and selects the subarea with the largest number of 1\´s to make a decision. The scan statistic integrates the aspect-dependence characteristic of the target into detection fusion. With a proper window size, it may suppress the subarea interference, and improve the system-level performance.