Cognitive radar network design and applications

PhD ThesisIn recent years, several emerging technologies in modern radar system design are attracting the attention of radar researchers and practitioners alike, noteworthy among which are multiple-input multiple-output (MIMO), ultra wideband (UWB) and joint communication-radar technologies. This thesis, in particular focuses upon a cognitive approach to design these modern radars. In the existing literature, these technologies have been implemented on a traditional platform in which the transmitter and receiver subsystems are discrete and do not exchange vital radar scene information. Although such radar architectures benefit from these mentioned technological advances, their performance remains sub-optimal due to the lack of exchange of dynamic radar scene information between the subsystems. Consequently, such systems are not capable to adapt their operational parameters “on the fly”, which is in accordance with the dynamic radar environment. This thesis explores the research gap of evaluating cognitive mechanisms, which could enable modern radars to adapt their operational parameters like waveform, power and spectrum by continually learning about the radar scene through constant interactions with the environment and exchanging this information between the radar transmitter and receiver. The cognitive feedback between the receiver and transmitter subsystems is the facilitator of intelligence for this type of architecture. In this thesis, the cognitive architecture is fused together with modern radar systems like MIMO, UWB and joint communication-radar designs to achieve significant performance improvement in terms of target parameter extraction. Specifically, in the context of MIMO radar, a novel cognitive waveform optimization approach has been developed which facilitates enhanced target signature extraction. In terms of UWB radar system design, a novel cognitive illumination and target tracking algorithm for target parameter extraction in indoor scenarios has been developed. A cognitive system architecture and waveform design algorithm has been proposed for joint communication-radar systems. This thesis also explores the development of cognitive dynamic systems that allows the fusion of cognitive radar and cognitive radio paradigms for optimal resources allocation in wireless networks. In summary, the thesis provides a theoretical framework for implementing cognitive mechanisms in modern radar system design. Through such a novel approach, intelligent illumination strategies could be devised, which enable the adaptation of radar operational modes in accordance with the target scene variations in real time. This leads to the development of radar systems which are better aware of their surroundings and are able to quickly adapt to the target scene variations in real time.Newcastle University, Newcastle upon Tyne: University of Greenwich

Discrimination of Angle-Doppler Signatures using Arbitrary Phase Center Motion for MIMO Radars

A novel Phase Center Motion (PCM) based technique for discriminating angle-Doppler signatures within Multiple-Input-Multiple-Output (MIMO) radars using Frequency Modulated Continuous Wave (FMCW) has been explored in this work. The PCM technique induces angle dependent Doppler shifts in the back-scattered signal, wherein a modified Doppler post processing for FMCW leads to joint angle-Doppler processing. Specifically, we intend to design unique spatialtemporal motion of the phase center on each individual MIMO radar channel in an effort to synthesize nearly orthogonal angle-Doppler signatures. Subsequently, we also develop a MIMO radar receiver design, which would be capable of discriminating between these induced angle-Doppler signatures. The asymptotic investigation provides a Bessel function characteristic. Simulation results demonstrate a significant side-lobe suppression of 8:5 dB for an individual PCM trajectory and 7 dB over distinct PCM trajectories, in an attempt towards realization of nearly orthogonal MIMO radar channels

Random Phase Center Motion Technique for Enhanced Angle-Doppler Discrimination Using MIMO Radars

A random Phase Center Motion (PCM) technique is presented in this paper, based on Frequency Modulated Continuous Wave (FMCW) radar, in order to suppress the angle- Doppler coupling in Time Division Multiplex (TDM) Multiple- Input-Multiple-Output (MIMO) radar when employing sparse array structures. The presented approach exploits an apparently moving transmit platform or PCM due to spatio-temporal transmit array modulation. In particular, the work considers a framework utilizing a random PCM trajectory. The statistical characterization of the random PCM trajectory is devised, such that the PCM and the target motion coupling is minimal, while the angular resolution is increased by enabling the virtual MIMO concept. In more details, this paper discusses sidelobe suppression approaches within the angle-Doppler Ambiguity Function (AF) by introducing a phase center probability density function within the array. This allows for enhanced discrimination of multiple targets. Simulation results demonstrate the suppression angle- Doppler coupling by more than 30 dB, even though spatiotemporal transmit array modulation is done across chirps which leads usually to strong angle-Doppler coupling

Vector precoding scheme for multi-user MIMO systems

In this paper, the performance of vector precoding in multiple input multiple output broadcast channels (MIMO BC) is investigated and compared with other channel decomposition techniques utilized for implementing zero forcing (ZF) preceding. It is a known result that ZF precoding requires pseudo inversion of the channel matrix, where this operation is only optimum when the transmitter power is unconstrained. The problem when the transmitter is subject to average or maximum power constraints is well known, where results published have indicated that ZF precoding approaches the maximum capacity bound if the dimensionality of the system is greater than the number of transmitter antennas. A vector precoding technique for MIMO BC channels is investigated in this paper where pseudo inversion is circumvented by employing joint co-operation between transmitter and receiver for all users. This technique adopts a time scheduling approach to service the users which facilitates decentralized multi-user detection at the receiver. This approach yields an improvement to the bit error rate probability by approximately an order of magnitude as compared to the ZF approach utilizing other channel decomposition techniques. The scheme also enables an increase in the capacity of the MIMO BC, with less computational complexity as compared to the techniques employing Moore-Penrose pseudo inverse

Open Collaborative Grid Services Architecture (OCGSA

In this paper we introduce a new architecture, called Open Collaborative Grid Service

Minimum cell size for information capacity increase in cellular wireless network

In this paper results of mathematical analysis supported by simulation are used to find a theoretical limit for cell size reduction in mobile communication systems. Information capacity approach is used for the analysis. Attention is given to the active co-channel interfering cells. Because at microwave frequencies beyond 2 GHz, co-channel interfering cells beyond the first tier becomes dominant as the cell size reduces. We show that when the cell size limit is reached any further reduction in cell size will not increase the information capacity of the cellular network. A formula is derived for calculating the number of co-channel cells in subsequent tiers

Hidden Markov model for target tracking with UWB radar systems

In this paper we demonstrate the application of Hidden Markov Models (HMM) for localization and tracking in ultra wide band (UWB) radar networks. To improve localization, a Voronoi region based approach is utilized to form a HMM for detection and tracking of mobile target. The observations used for the HMM localization are obtained from the power delay profile of the received signals. In UWB systems the use of entire power delay profiles instead of the total power only, allows to reach higher localization accuracy. This is due to the power delay profile being a measure of the power as well as the time of arrival. Simulation results suggest a performance gain of 7dB over the maximum likelihood estimation for localization in presence of path loss at intermediate values of signal to noise ratio (SNR)

Improved UWB Radar Signal Processing for the Extraction of Vital Parameters

The availability of contactless sensors capable of detecting vital parameters is of particular interest, especially when it is requested to ensure the patient’s freedom of movement, or when the patient’s physical conditions do not allow the application of sensing devices on the skin. Thanks to its characteristics of high spatial resolution and tissues penetration, an UltraWide Band radar system can be used for the measurement of respiratory and heart rates of hospitalized patients. As typical of radar systems, however, the useful echo is superimposed to a multiplicity of unwanted echoes, due to reflection by obstacles, normally fixed, that may be present in the environment considered. Among the various techniques proposed in the literature, this work presents an enhanced processing of the signal received by an Ultra Wide Band radar, in the presence of static echoes, the magnitude of which may be also considerably higher than the level of the signals reflected by the target. The simulation results show the effectiveness of the proposed processing method, and its sensitivity to the radar system design parameters

Information-theoretic algorithm for waveform optimization within ultra wideband cognitive radar network

A novel information-theoretic approach for designing the excitation ultra wideband (UWB) waveforms within a cognitive radar network is developed. This method utilizes the mutual information (MI) between subsequent radar returns to extract desired information from the radar scene. With this approach, the radar system constantly learns about its surroundings and adopts its operational mode accordingly based upon the MI minimization criterion. Subsequently, the positioning algorithm makes use of this information about the radar scene to generate more accurate location estimates. Numerical results demonstrate an improvement in the probability of target detection even at low values of receive signal-to-noise ratio (SNR). The proposed algorithm also promises a better delay-Doppler resolution of the target, which can be analyzed through the radar ambiguity function (AF). Simulation data show an improvement in the target discrimination ability in the presence of noise and clutter