Phase tracking with a cognitive Antijam Receiver System (CARS)

Abstract

Existing antijam (AJ) and interference mitigation techniques are based on the assumption that the nature of interference is known a-priori. Generally, one or more fixed antijam techniques (FATs) are applied to reduce the impact of the jammer or interferer to a receiver. A more general approach is to apply cognitive radio technology, whereby the receiver's AJ processing and receiver processing adapt to the incoming interference, in an approach known as a Cognitive Antijam Receiver System (CARS). Code and carrier tracking can be quite challenging when the presence of interference is significant. On this paper we will study the problem of carrier and code tracking under these conditions and show how a CARS mitigation approach can benefit overall performance. Tracking jitter will be the primary metric used in this optimization. By analyzing tracking and data demodulation performance in response to an interference signal, we propose an algorithm to select and adapt the receiver parameters as a function of the interferer signal properties. Simulation results show that the CARS approach allows data demodulation and tracking even under severe interference conditions, whereas FATs approaches fail to achieve such performance levels.