Development of Novel Techniques For Passive Radar With Waveform Design, Tracking and Sequential Fusion

Abstract

In modern warfare, electronic countermeasure (ECM) approaches have gained much importance as electronic technology and military intelligence has improved signifi- cantly. The common forms of ECM are noise jamming and deception jamming. Noise jamming is an ECM technique, in which the target radar sends a stronger noise sig- nal at the operational frequency of the radar, blending the target’s signature entirely with the interference. Deception jamming techniques, on the other hand, such as range gate pull-off (RGPO) and velocity gate pull-off (VGPO), are the most effective of all ECM techniques for creating false targets to misguide the target tracking sys- tems. RGPO ECM intercepts the radar signals and retransmits a deception signal with a progressive time delay, pulling the range gate of the radar target tracker further away from the actual target over time. The main focus of this research work is to combat the range deception ECM using the effective electronic counter countermea- sure (ECCM) technique. Further, the research is focused on passive radars, which have the advantage of covertness and cost-effectiveness and are useful in military and civilian applications. Furthermore, the secondary objective of this research work is to comprehensively analyze the performance of existing illuminators of opportunity (IOO) and propose a good IOO for passive radars. Primarily, the first objective proposes a sequential fusion-based approach for de- tecting the range deception ECM and estimating the RGPO deception parameter of the deceived local track in a networked radar system (NRS). In NRS, each radar has a local tracker that provides local estimates (updated state and covariance), which are subsequently forwarded to the fusion node. Following that, a track-to-track asso- ciation (T2TA) at the fusion node is formed to detect the deceived tracks utilizing all accessible local tracks. For the deceived track, the pseudo-measurements are created using the inverse Kalman filter-based tracklets. Further, the reference measurements are created by sequentially fusing all the undeceived local tracks. Next, the recursive least squares estimator (RLSE) is used to estimate the range deception parameter of the deceived track using the pseudo-measurements and the reference measurements. Furthermore, the proposed deception parameter estimation algorithm is also analyzed ifor single and multiple RGPO ECM scenarios. Moreover, the Cramer Rao Lower Bound (CRLB) is derived for the proposed estimation algorithm. Also, Position Root Mean Square Error (PRMSE), CRLB, innovation test, normalized estimation error squared (NEES) test, and confidence interval are used to quantify the results. The simulation results highlight that the proposed estimation algorithm provides improved performance in the presence of RGPO ECM. Besides, it is evident from the results that estimator efficiency is falling below the 5% tail probability of the chi-square distribution. Another contribution of the thesis is to carry out the feasibility study of the 5G New Radio (5G NR) waveform as an IOO for passive radar. The investigation results show the possibility of utilizing the 5G NR waveform as a suitable IOO for target detection in passive radar applications. For the 5G NR waveform, parameters like range resolution and velocity resolution are determined, and a comparison is made with the LTE waveform. The simulation results reveal that the 5G NR waveform pro- vides better range resolution and velocity resolution than the LTE and other IOOs. Further, Significant recent radar research has been focused on knowledge-aided signal processing, waveform design, detection, and target-tracking applications. The knowl- edge related to the illuminator of opportunity (IOO) selection, spectrum sensing, and diversity technique can predominantly improve the received signal strength (RSS) at the passive radar receiver. In addition, this work proposes a conceptual framework to build knowledge-aided passive radar systems (KA-PRS) based on spectrum sensing, IOO selection, and spatial diversity. Finally, this research investigation proposes a comprehensive analysis of losses in- curred by the IOOs during their propagation in the surveillance environment. The dif- ferent IOOs considered in this investigation are Frequency Modulated (FM) waveform, Digital Video Broadcasting (DVB) waveform, Long Term Evolution (LTE) Waveform, and 5G NR waveform, etc. The atmospheric losses (such as path loss, rain loss, gas loss, fog loss, and foliage loss) are analyzed for various IOOs. Further, signal-to-noise ratio analysis for 5G NR waveform at FR1 and FR2 frequencies is carried out in the presence of atmospheric losses. The simulation results show that the high frequency 5G NR FR2 waveform (26 GHz to 50 GHz) suffers significantly higher losses than other IOOs, even though it provides improved range and velocity resolution. Specif- iiically, the 5G New Radio waveform for FR1 and FR2 frequencies has 10% and 20% more losses than the LTE waveform. On the other hand, the FM waveform suffers insignificant losses compared to other IOOs despite the poor range and velocity reso- lution. Additionally, the penetration loss for common building materials such as clear glass, plywood, and tile for the 5G NR FR1 frequency, LTE signal frequency, and Wi-Fi is measured using the Texas Instruments AFE7950 radar sensor. Further, the results obtained in this contribution can be a valuable reference for passive bistatic radar as the comprehensive analysis includes all IOOs along with the newly proposed 5G NR waveform. Overall, this thesis proposes a potential ECCM technique to overcome the effect of range deception ECM in the target tracking framework. Further, the feasibility of utilizing 5G NR for passive radar is carried out along with the comprehensive study of losses for various IOOs.