Skip to Main Content
A model-based detector decides on a change from the normal mode after it adaptively monitors the environment. If the state of the system follows the model that is predicted by the model-based processor, we say that the system is in the normal mode. Since the sensor arrays are used for such processings, the array signal processing concepts are widely used in these systems. Because of continues change in the environment for the active or passive sonar-type systems, a model-based detector can offer a considerable detection in this case. Two main parts in the design procedure of a model-based detector is to estimate/update the model parameters and the mismatch detection of the model. In this paper, we consider the mismatch detection in such a detector, that utilizes an array of sensors for data gathering. Using the condition number of the correlation matrix of innovations, we propose a fast detector scheme. Some simulation examples are used to evaluate the performance of the proposed detector. We test and compare the performance of our detector, while some parameters are changing.