Passive detection of moving aerial target based on multiple collaborative GPS satellites

Passive localization is an important part of intelligent surveillance in security and emergency applications. Nowadays, Global Navigation Satellite Systems (GNSSs) have been widely deployed. As a result, the satellite signal receiver may receive multiple GPS signals simultaneously, incurring echo signal detection failure. Therefore, in this paper, a passive method leveraging signals from multiple GPS satellites is proposed for moving aerial target detection. In passive detection, the first challenge is the interference caused by multiple GPS signals transmitted upon the same spectrum resources. To address this issue, successive interference cancellation (SIC) is utilized to separate and reconstruct multiple GPS signals on the reference channel. Moreover, on the monitoring channel, direct wave and multi-path interference are eliminated by extensive cancellation algorithm (ECA). After interference from multiple GPS signals is suppressed, the cycle cross ambiguity function (CCAF) of the signal on the monitoring channel is calculated and coordinate transformation method is adopted to map multiple groups of different time delay-Doppler spectrum into the distance−velocity spectrum. The detection statistics are calculated by the superposition of multiple groups of distance-velocity spectrum. Finally, the echo signal is detected based on a properly defined adaptive detection threshold. Simulation results demonstrate the effectiveness of our proposed method. They show that the detection probability of our proposed method can reach 99%, when the echo signal signal-to-noise ratio (SNR) is only −64 dB. Moreover, our proposed method can achieve 5 dB improvement over the detection method using a single GPS satellite

Fundamental Limits on Performance for Cooperative Radar-Communications Coexistence

abstract: Spectral congestion is quickly becoming a problem for the telecommunications sector. In order to alleviate spectral congestion and achieve electromagnetic radio frequency (RF) convergence, communications and radar systems are increasingly encouraged to share bandwidth. In direct opposition to the traditional spectrum sharing approach between radar and communications systems of complete isolation (temporal, spectral or spatial), both systems can be jointly co-designed from the ground up to maximize their joint performance for mutual benefit. In order to properly characterize and understand cooperative spectrum sharing between radar and communications systems, the fundamental limits on performance of a cooperative radar-communications system are investigated. To facilitate this investigation, performance metrics are chosen in this dissertation that allow radar and communications to be compared on the same scale. To that effect, information is chosen as the performance metric and an information theoretic radar performance metric compatible with the communications data rate, the radar estimation rate, is developed. The estimation rate measures the amount of information learned by illuminating a target. With the development of the estimation rate, standard multi-user communications performance bounds are extended with joint radar-communications users to produce bounds on the performance of a joint radar-communications system. System performance for variations of the standard spectrum sharing problem defined in this dissertation are investigated, and inner bounds on performance are extended to account for the effect of continuous radar waveform optimization, multiple radar targets, clutter, phase noise, and radar detection. A detailed interpretation of the estimation rate and a brief discussion on how to use these performance bounds to select an optimal operating point and achieve RF convergence are provided.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Full-Duplex OFDM Radar With LTE and 5G NR Waveforms: Challenges, Solutions, and Measurements

This paper studies the processing principles, implementation challenges, and performance of OFDM-based radars, with particular focus on the fourth-generation Long-Term Evolution (LTE) and fifth-generation (5G) New Radio (NR) mobile networks' base stations and their utilization for radar/sensing purposes. First, we address the problem stemming from the unused subcarriers within the LTE and NR transmit signal passbands, and their impact on frequency-domain radar processing. Particularly, we formulate and adopt a computationally efficient interpolation approach to mitigate the effects of such empty subcarriers in the radar processing. We evaluate the target detection and the corresponding range and velocity estimation performance through computer simulations, and show that high-quality target detection as well as high-precision range and velocity estimation can be achieved. Especially 5G NR waveforms, through their impressive channel bandwidths and configurable subcarrier spacing, are shown to provide very good radar/sensing performance. Then, a fundamental implementation challenge of transmitter-receiver (TX-RX) isolation in OFDM radars is addressed, with specific emphasis on shared-antenna cases, where the TX-RX isolation challenges are the largest. It is confirmed that from the OFDM radar processing perspective, limited TX-RX isolation is primarily a concern in detection of static targets while moving targets are inherently more robust to transmitter self-interference. Properly tailored analog/RF and digital self-interference cancellation solutions for OFDM radars are also described and implemented, and shown through RF measurements to be key technical ingredients for practical deployments, particularly from static and slowly moving targets' point of view.Comment: Paper accepted by IEEE Transactions on Microwave Theory and Technique

Analysis and Design of Joint Communication and Sensing for Wireless Cellular Networks

Joint communication and sensing (JCAS) has emerged as an important piece of technology that will radically change ordinary wireless communication and radar systems. This research area, which has significantly grown over the last decade, aims to develop integrated systems that can provide both communication and sensing/radar functionalities simultaneously. The convergence of both systems into the same joint platform facilitates a more efficient use of the hardware and spectrum resources, enabling new civilian and professional applications. This thesis focuses on the integration of JCAS functionalities into mobile cellular networks, such as fifth-generation new radio (5G NR) and sixth generation (6G) communication systems, which are developing toward higher frequency ranges at millimeter-wave (mm-wave) bands, coming with wider bandwidths, and have massive antenna arrays, providing a great framework to develop sensing functionalities. By implementing JCAS, the different nodes of the cellular network, such as the base station and user equipment, can sense and reconstruct their surroundings. However, the JCAS operation yields multiple design challenges that need to be addressed. To this end, this thesis aims to develop novel algorithms in two relevant research areas that comprise self-interference (SI) cancellation and beamforming optimization techniques for JCAS systems. This work analyzes the potential sensing performance of mobile cellular networks, proposing a joint framework and identifying the main radar processing techniques to support JCAS. The fundamental SI challenge stemming from the simultaneous operation of the transmitter and receiver is investigated, and different JCAS cancellation techniques are proposed. The performance and feasibility of the proposed JCAS system is evaluated through simulation and measurement experiments at different frequency bands and scenarios, identifying mm-wave frequencies as the key enabler for future JCAS systems. Alternative antenna architectures and beamforming methods for mm-wave JCAS platforms are proposed by considering both communication and sensing requirements. Specifically, this thesis proposes novel beamforming methods that provide multiple beams, supporting efficient beamformed communications while an additional beam senses the environment simultaneously. In addition, the proposed beam-forming algorithms address the SI challenge by implementing an efficient spatial suppression scheme to suppress the direct transmitter–receiver coupling

Integrated Sensing and Communication for 6G: Ten Key Machine Learning Roles

Integrating sensing and communication is a defining theme for future wireless systems. This is motivated by the promising performance gains, especially as they assist each other, and by the better utilization of the wireless and hardware resources. Realizing these gains in practice, however, is subject to several challenges where leveraging machine learning can provide a potential solution. This article focuses on ten key machine learning roles for joint sensing and communication, sensing-aided communication, and communication-aided sensing systems, explains why and how machine learning can be utilized, and highlights important directions for future research. The article also presents real-world results for some of these machine learning roles based on the large-scale real-world dataset DeepSense 6G, which could be adopted in investigating a wide range of integrated sensing and communication problems.Comment: Submitted to IEE

Waveform Diversity and Range-Coupled Adaptive Radar Signal Processing

Waveform diversity may offer several benefits to radar systems though often at the cost of reduced sensitivity. Multi-dimensional processing schemes are known to offer many degrees of freedom, which can be exploited to suppress the ambiguity inherent to pulse compression, array processing, and Doppler frequency estimation. Spatial waveform diversity can be achieved by transmitting different but correlated waveforms from each element of an antenna array. A simple yet effective scheme is employed to transmit different waveforms in different spatial directions. A new reiterative minimum mean squared error approach entitled Space-Range Adaptive Processing, which adapts simultaneously in range and angle, is derived and shown in simulation to offer enhanced performance when spatial waveform diversity is employed relative to both conventional matched filtering and sequentially adapting in angle and then range. The same mathematical framework is utilized to develop Time-Range Adaptive Processing (TRAP) algorithm which is capable of simultaneously adapting in Doppler frequency and range. TRAP is useful when pulse-to-pulse changing of the center frequency or waveform coding is used to achieve enhanced range resolution or unambiguous ranging, respectively. The inherent computational complexity of the new multi-dimensional algorithms is addressed by segmenting the full-dimension cost functions, yielding a reduced-dimensional variants of each. Finally, a non-adaptive approach based on the multi-dimensional TRAP signal model is utilized to develop an efficient clutter cancellation technique capable of suppressing multiple range intervals of clutter when waveform diversity is applied to pulse-Doppler radar

FM airborne passive radar

The airborne application of Passive Bistatic Radar (PBR) is the latest evolution of the now established international interest in passive radar techniques. An airborne passive system is cheaper to construct, easier to cool, lighter and requires less power than a traditional active radar system. These properties make it ideal for installation on an Unmanned Aerial Vehicle (UAV), especially for the next generation of Low Observable (LO) UAVs, complementing the platforms LO design with an inherently Low Probability of Intercept (LPI) air-to-air and air-to-ground sensing capability. A comprehensive literature review identified a lack of practical and theoretical research in airborne passive bistatic radar and a quantitative model was designed in order to un- derstand the theoretical performance achievable using a hypothetical system and FM as the illuminator of opportunity. The results demonstrated a useable surveillance volume, assuming conservative estimates for the receiver parameters and allowed the scoping and specification of an airborne demonstrator system. The demonstrator system was subsequently designed and constructed and flown on airborne experiments to collect data for both air-to-air and air-to-ground operation analysis. Subsequent processing demonstrated the successful detection of air targets which correlated with the actual aircraft positions as recorded by a Mode-S/ADS-B receiver. This is the first time this has been conclusively demonstrated in the literature. Doppler Beam Sharpening was used to create a coarse resolution image allowing the normalised bistatic clutter RCS of the stationary surface clutter to be analysed. This is the first time this technique has been applied to an airborne passive system and has yielded the first quantitive values of normalised bistatic clutter RCS at VHF. This successful demonstration of airborne passive radar techniques provides the proof of concept and identifies the key research areas that need to be addressed in order to fully develop this technology

Using heterogeneous satellites for passive detection of moving aerial target

Passive detection of a moving aerial target is critical for intelligent surveillance. Its implementation can use signals transmitted from satellites. Nowadays, various types of satellites co-exist which can be used for passive detection. As a result, a satellite signal receiver may receive signals from multiple heterogeneous satellites, causing difficult in echo signal detection. In this paper, a passive moving aerial target detection method leveraging signals from multiple heterogeneous satellites is proposed. In the proposed method, a plurality of direct wave signals is separated in a reference channel first. Then, an adaptive filter with normalized least-mean-square (NLMS) is adopted to suppress direct-path interference (DPI) and multi-path interference (MPI) in a surveillance channel. Next, the maximum values of the cross ambiguity function (CAF) and the fourth order cyclic cumulants cross ambiguity function (FOCCCAF) correspond into each separated direct wave signal and echo signal will be utilized as the detection statistic of each distributed sensor. Finally, final detection probabilities are calculated by decision fusion based on results from distributed sensors. To evaluate the performance of the proposed method, extensive simulation studies are conducted. The corresponding simulation results show that the proposed fusion detection method can significantly improve the reliability of moving aerial target detection using multiple heterogeneous satellites. Moveover, we also show that the proposed detection method is able to significantly improve the detection performance by using multiple collaborative heterogeneous satellites