Hybrid Cognitive Phased and Frequency Diverse Array Radar

Abstract

Hybrid designs in modern radar technology have drawn significant consideration of research community. They have got numerous advantages over stand-alone models. The prominent stand-alone radar models include phased array radar (PAR), frequency diverse array radar (FDA) and cognitive radar (CR). The PAR generates an energy focused beam pattern towards desired direction and has an ability to suppress interferences. An FDA radar provides additional degrees-of-freedom and generates a 3-D range-angle dependent beam pattern. Similarly, a CR adjusts the design parameters onthe-fly using situational awareness ability. The work presented in this dissertation include the hybrid designs of CR with PAR and FDA that combines the benefits of either sides. The work is primarily divided into two parts. First part contains a novel hybrid design of CR with PAR i.e., hybrid cognitive phased array radar (HCPAR). This radar model contains the benefits of both sides. A low probability of intercept (LPI) property with transmit beamforming is also incorporated in the proposed design. The performance of proposed model is analyzed on the basis of situational awareness, which is proved to be an important parameter. The proposed hybrid design shows better signal to interference and noise ratio (SINR) and detection probability as compared to conventional stand-alone PAR model. Moreover, this design is energy efficient compared to previous models due to the reason that it illuminates only the region in vicinity of target predicted position received as feedback. In second part of the work, a novel hybrid model of CR with FDA is presented i.e., hybrid cognitive frequency diverse array (HCFDA) radar. The objective is to combine the benefits of both sided for improved target localization and tracking performance. This hybrid design is further divided into two categories. In first category, the HCFDA design with uniform frequency offset is analyzed. In this case, a uniform frequency offset for an FDA transmitter is computed based on the receiver feedback. Situational awareness of the proposed design helps to improve SINR, detection probability and energy efficiency as compared to conventional stand-alone designs. In second category, the HCFDA design is proposed with non-uniform frequency offsets. The non-uniform frequency offsets are computed based on the receiver feedback using four different methods i.e., i) mu-law companding formulae based offsets, ii) Hamming window based tapering offsets, iii) Genetic algorithm (GA) based fractional offsets and iv) non-uniform but integer frequency offsets. To analyze the performance of proposed designs, the situational awareness along with the non-uniform offsets, computed using various methods, have proved to be an important basis. The proposed designs achieve better SINR, detection probability, energy efficiency and improved Cramer Rao lower bound (CRLB) on range and angle estimations as compared to conventional stand-alone FDA design. The proposed designs also provide improved transmit energy focusing towards target position, which results in improved range and angle resolution as compared to the existing designs. The proposed hybrid designs provide a strong base for the development of modern radar generations with intelligent target steering ability in space. At present, the proposed schemes are investigated only for linear array, yet they can be extended to planar arrays and other topologies according to the requirement.