Detection and Tracking of Radar Targets With In-Band Communication Interference for Radcomm Spectrum Sharing

Abstract

The problem of spectral congestion considers radar and communication system (Rad- Comm) spectrum sharing as an inevitable solution. As these systems share the spec- trum, they cause interference to one another. Many researchers started suggesting various solutions to address the in-band interference. Towards this step, addressing the problem from the radar perspective, this thesis makes two primary contributions. The first one is detecting the target-reflected radar signals in the presence of inter- ference from an in-band cyclostationary digital modulated wireless communication signal. The Neyman-Pearson (NP) based optimum detection rules have been derived for the equalization of the interference from in-band communication systems. Sub- optimum detection structures are also derived with the assumption that the in-band interference is a white stationary time-invariant Gaussian process. Further, consid- ering the equalization, modified CFAR receiver structures are also presented. By considering the mathematical models for cyclostationary or periodic in-band interfer- ence, the performances of the optimum, sub-optimum and modified CFAR detectors are quantified analytically in terms of detection and false alarm probabilities. The resulting receiver operating characteristic (ROC) curves are analysed as a function of the signal-to-interference ratio (SIR). Another important contribution considered in this research investigation is target tracking performance of a radar system in the presence of in-band wireless commu- nication transmitters (IWCTs). The distributed radars present in the surveillance region surrounded by multiple in-band wireless communication transmitters (IWCTs) scenario is considered. A new measurement model is proposed by considering both radar returns and returns due to IWCTs. The tracking performance is evaluated using the global nearest neighbour (GNN) tracker with an extended Kalman filter (EKF) for the received measurement set. The track-to-track association (T2TA) is performed to identify the true target track on multiple tracks produced owing to the presence of IWCTs. The track-to-track fusion (T2TF) is carried out to improve the true tar- get estimates. The position root mean square error (PRMSE) is used to quantify the target estimation accuracy. The posterior Cramer–Rao lower bounds (PCRLBs) iquantifying the achievable estimation accuracies are also presented. The simulation results reveal that the T2TA of tracks from multiple radars identify the true target track, and T2TF improves the PRMSE. As an additional third contribution, the spectrum sharing radar (SSR) is consid- ered that uses the total available bandwidth (BW) for both radar-based sensing and communication. Unlike traditional radar, the SSR divides the total available BW into radar-only and mixed-use bands. Taking such BW sharing into account, this research investigates the performance of SSR in an information-theoretic sense. To evalu- ate performance, mutual information (MI), spectral efficiency (SE), and capacity (C) metrics are used. Initially, a clean environment (no multipath) is considered in order to evaluate performance metrics in the mixed-use band with and without successive interference cancellation (SIC). The MI and SE are calculated in the mixed-use band with and without successive interference cancellation (SIC). Also, the performance metrics are extended to account for the multipath environment. In addition, the MI, SE, and C of traditional radar and communication systems are taken into account to compare the performance of SSR. Furthermore, this research presents target estimation performance improvement in the cooperative RadComm spectrum sharing system model. Due to cooperation, target returns results from the communication transmitter are also exploited to im- prove the target estimation performance. The Cramer-Rao lower bound (CRLB) is considered as a metric to evaluate the target estimation performance. The co- operative system model is compared with the non-cooperative RadComm spectrum sharing operation and stand-alone radar system operation. Simulation results reveals that the cooperative RadComm spectrum sharing system model provides improved performance compared to non-cooperative and stand-alone operations.