Range and velocity estimations in multi-band hybrid multistatic radar networks

This study investigates the benefits of exploiting multiple illuminators of opportunity (IOs) in hybrid radar systems consisting of multi-band receivers that can utilise active radar waveforms and broadcasting signals for multistatic radar sensing. As a performance metric, Cramér-Rao lower bounds (CRLBs) on the range and velocity estimations are considered. FM radio, Digital Video Broadcasting-Terrestrial (DVB-T) and Digital Audio Broadcasting (DAB) transmitters are considered as IOs for passive radar sensing while also having an active radar transmitter in the multistatic radar network. The multistatic radar networks consisting of receivers, transmitters and IOs are modelled and simulated and CRLBs on the range and velocity estimations are calculated. Two different multistatic radar network scenarios are simulated and the results are evaluated to analyse the estimation accuracy of active and passive bistatic pairs. The results show that a multi-band multistatic radar network can provide better range and velocity estimations by exploiting IO signals compared to a radar network that only uses traditional active radar waveforms

Jamming Effects on Hybrid Multistatic Radar Network Range and Velocity Estimation Errors

This research studies the effects of three noise jamming techniques on the performance of a hybrid multistatic radar network in a selection of different electronic warfare (EW) situations. The performance metrics investigated are the range and velocity estimation errors found using the Cramér-Rao lower bounds (CRLBs). The hybrid multistatic network simulated is comprised of a single active radar transmitter, three illuminators of opportunity (IO), a receiver co-located at the active transmitter site, and two separately located silent receivers. Each IO transmits at a unique frequency band commonly used for civilian applications, including Digital Video Broadcasting-Terrestrial (DVB-T), Digital Audio Broadcasting (DAB), and FM radio. Each receiver is capable of receiving signals at all three IO frequency bands as well as the operating frequency band of the active radar transmitter. The investigations included compare the performance of the network at detecting a single flying target under conditions where different combinations of jammer type, operating mode, directivity, and number of jammers operating are used. The performance degradation of the system compared to operation in a non-contested environment is determined and a comparison between the performance of the hybrid multistatic radar with that achievable by a monostatic radar and an active-only multistatic radar network within a selection of contested scenarios is made. Results show that the use of spatially distributed nodes and frequency diversity within the system enable greater theoretical functionality in the presence of jamming over conventional radar systems

Exploiting Sparse Structures in Source Localization and Tracking

This thesis deals with the modeling of structured signals under different sparsity constraints. Many phenomena exhibit an inherent structure that may be exploited when setting up models, examples include audio waves, radar, sonar, and image objects. These structures allow us to model, identify, and classify the processes, enabling parameter estimation for, e.g., identification, localisation, and tracking.In this work, such structures are exploited, with the goal to achieve efficient localisation and tracking of a structured source signal. Specifically, two scenarios are considered. In papers A and B, the aim is to find a sparse subset of a structured signal such that the signal parameters and source locations maybe estimated in an optimal way. For the sparse subset selection, a combinatorial optimization problem is approximately solved by means of convex relaxation, with the results of allowing for different types of a priori information to be incorporated in the optimization. In paper C, a sparse subset of data is provided, and a generative model is used to find the location of an unknown number of jammers in a wireless network, with the jammers’ movement in the network being tracked as additional observations become available

Performance Analysis of Bearings-only Tracking Problems for Maneuvering Target and Heterogeneous Sensor Applications

State estimation, i.e. determining the trajectory, of a maneuvering target from noisy measurements collected by a single or multiple passive sensors (e.g. passive sonar and radar) has wide civil and military applications, for example underwater surveillance, air defence, wireless communications, and self-protection of military vehicles. These passive sensors are listening to target emitted signals without emitting signals themselves which give them concealing properties. Tactical scenarios exists where the own position shall not be revealed, e.g. for tracking submarines with passive sonar or tracking an aerial target by means of electro-optic image sensors like infrared sensors. This estimation process is widely known as bearings-only tracking. On the one hand, a challenge is the high degree of nonlinearity in the estimation process caused by the nonlinear relation of angular measurements to the Cartesian state. On the other hand, passive sensors cannot provide direct target location measurements, so bearings-only tracking suffers from poor target trajectory estimation accuracy due to marginal observability from sensor measurements. In order to achieve observability, that means to be able to estimate the complete target state, multiple passive sensor measurements must be fused. The measurements can be recorded spatially distributed by multiple dislocated sensor platforms or temporally distributed by a single, moving sensor platform. Furthermore, an extended case of bearings-only tracking is given if heterogeneous measurements from targets emitting different types of signals, are involved. With this, observability can also be achieved on a single, not necessarily moving platform. In this work, a performance bound for complex motion models, i.e. piecewisely maneuvering targets with unknown maneuver change times, by means of bearings-only measurements from a single, moving sensor platform is derived and an efficient estimator is implemented and analyzed. Furthermore, an observability analysis is carried out for targets emitting acoustic and electromagnetic signals. Here, the different signal propagation velocities can be exploited to ensure observability on a single, not necessarily moving platform. Based on the theoretical performance and observability analyses a distributed fusion system has been realized by means of heterogeneous sensors, which shall detect an event and localize a threat. This is performed by a microphone array to detect sound waves emitted by the threat as well as a radar detector that detects electromagnetic emissions from the threat. Since multiple platforms are involved to provide increased observability and also redundancy against possible breakdowns, a WiFi mobile ad hoc network is used for communications. In order to keep up the network in a breakdown OLSR (optimized link state routing) routing approach is employed

Passiivisen tutkan järjestelmämuutosten vaikutukset toimintaalueeseen

Passive radar has in general a coverage much more complex than that of a tradition radar. Predicting the coverage and therefore the areas lacking vision is time-consuming to compute with reasonable accuracy, and requires complete recalculations if the system topology changes. In this work a generalised Cramér-Rao bound for joint position and velocity estimations is used to compute an unbiased estimator parameter variance lower bound. The estimations are combined in differing ways to qualitatively mimic modularised coverage in case of topological change. The combinations and full single-simulation results are compared by the area limited by a chosen lower bound. The areal differences in single computations versus partitionedly computed predictions range from subtle to significant. The type of change and system configuration seem to have the most effect on the accuracy, since some predictions achieve less that 10% difference regardless of the bound. Primarily the methods evaluated did not achieve desirable results, and the outcome could be described as a suggestive outline of the way to approach the problem in further research. Not much could be said about the feasibility of similar modularisation without validated data, and more in-depth analysis of the lower bound

Integrated Sensing and Communications: Recent Advances and Ten Open Challenges

It is anticipated that integrated sensing and communications (ISAC) would be one of the key enablers of next-generation wireless networks (such as beyond 5G (B5G) and 6G) for supporting a variety of emerging applications. In this paper, we provide a comprehensive review of the recent advances in ISAC systems, with a particular focus on their foundations, system design, networking aspects and ISAC applications. Furthermore, we discuss the corresponding open questions of the above that emerged in each issue. Hence, we commence with the information theory of sensing and communications (S$\&$C), followed by the information-theoretic limits of ISAC systems by shedding light on the fundamental performance metrics. Next, we discuss their clock synchronization and phase offset problems, the associated Pareto-optimal signaling strategies, as well as the associated super-resolution ISAC system design. Moreover, we envision that ISAC ushers in a paradigm shift for the future cellular networks relying on network sensing, transforming the classic cellular architecture, cross-layer resource management methods, and transmission protocols. In ISAC applications, we further highlight the security and privacy issues of wireless sensing. Finally, we close by studying the recent advances in a representative ISAC use case, namely the multi-object multi-task (MOMT) recognition problem using wireless signals.Comment: 26 pages, 22 figures, resubmitted to IEEE Journal. Appreciation for the outstanding contributions of coauthors in the paper

Quantum Communication, Sensing and Measurement in Space

The main theme of the conclusions drawn for classical communication systems operating at optical or higher frequencies is that there is a well‐understood performance gain in photon efficiency (bits/photon) and spectral efficiency (bits/s/Hz) by pursuing coherent‐state transmitters (classical ideal laser light) coupled with novel quantum receiver systems operating near the Holevo limit (e.g., joint detection receivers). However, recent research indicates that these receivers will require nonlinear and nonclassical optical processes and components at the receiver. Consequently, the implementation complexity of Holevo‐capacityapproaching receivers is not yet fully ascertained. Nonetheless, because the potential gain is significant (e.g., the projected photon efficiency and data rate of MIT Lincoln Laboratory's Lunar Lasercom Demonstration (LLCD) could be achieved with a factor‐of‐20 reduction in the modulation bandwidth requirement), focused research activities on ground‐receiver architectures that approach the Holevo limit in space‐communication links would be beneficial. The potential gains resulting from quantum‐enhanced sensing systems in space applications have not been laid out as concretely as some of the other areas addressed in our study. In particular, while the study period has produced several interesting high‐risk and high‐payoff avenues of research, more detailed seedlinglevel investigations are required to fully delineate the potential return relative to the state‐of‐the‐art. Two prominent examples are (1) improvements to pointing, acquisition and tracking systems (e.g., for optical communication systems) by way of quantum measurements, and (2) possible weak‐valued measurement techniques to attain high‐accuracy sensing systems for in situ or remote‐sensing instruments. While these concepts are technically sound and have very promising bench‐top demonstrations in a lab environment, they are not mature enough to realistically evaluate their performance in a space‐based application. Therefore, it is recommended that future work follow small focused efforts towards incorporating practical constraints imposed by a space environment. The space platform has been well recognized as a nearly ideal environment for some of the most precise tests of fundamental physics, and the ensuing potential of scientific advances enabled by quantum technologies is evident in our report. For example, an exciting concept that has emerged for gravity‐wave detection is that the intermediate frequency band spanning 0.01 to 10 Hz—which is inaccessible from the ground—could be accessed at unprecedented sensitivity with a space‐based interferometer that uses shorter arms relative to state‐of‐the‐art to keep the diffraction losses low, and employs frequency‐dependent squeezed light to surpass the standard quantum limit sensitivity. This offers the potential to open up a new window into the universe, revealing the behavior of compact astrophysical objects and pulsars. As another set of examples, research accomplishments in the atomic and optics fields in recent years have ushered in a number of novel clocks and sensors that can achieve unprecedented measurement precisions. These emerging technologies promise new possibilities in fundamental physics, examples of which are tests of relativistic gravity theory, universality of free fall, frame‐dragging precession, the gravitational inverse‐square law at micron scale, and new ways of gravitational wave detection with atomic inertial sensors. While the relevant technologies and their discovery potentials have been well demonstrated on the ground, there exists a large gap to space‐based systems. To bridge this gap and to advance fundamental‐physics exploration in space, focused investments that further mature promising technologies, such as space‐based atomic clocks and quantum sensors based on atom‐wave interferometers, are recommended. Bringing a group of experts from diverse technical backgrounds together in a productive interactive environment spurred some unanticipated innovative concepts. One promising concept is the possibility of utilizing a space‐based interferometer as a frequency reference for terrestrial precision measurements. Space‐based gravitational wave detectors depend on extraordinarily low noise in the separation between spacecraft, resulting in an ultra‐stable frequency reference that is several orders of magnitude better than the state of the art of frequency references using terrestrial technology. The next steps in developing this promising new concept are simulations and measurement of atmospheric effects that may limit performance due to non‐reciprocal phase fluctuations. In summary, this report covers a broad spectrum of possible new opportunities in space science, as well as enhancements in the performance of communication and sensing technologies, based on observing, manipulating and exploiting the quantum‐mechanical nature of our universe. In our study we identified a range of exciting new opportunities to capture the revolutionary capabilities resulting from quantum enhancements. We believe that pursuing these opportunities has the potential to positively impact the NASA mission in both the near term and in the long term. In this report we lay out the research and development paths that we believe are necessary to realize these opportunities and capitalize on the gains quantum technologies can offer

Low-complexity three-dimensional AOA-cross geometric center localization methods via multi-UAV network

The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. The first method could estimate the source position and angle measurement noise at the same time by seeking the center of an inscribed sphere, called the CIS. Firstly, every sensor measures two angles, the azimuth angle and the elevation angle. Based on that, two planes are constructed. Then, the estimated values of the source position and the angle noise are achieved by seeking the center and radius of the corresponding inscribed sphere. Deleting the estimation of the radius, the second algorithm, called MSD-LS, is born. It is not able to estimate angle noise but has lower computational complexity. Theoretical analysis and simulation results show that proposed methods could approach the Cramér–Rao lower bound (CRLB) and have lower complexity than the MLE

MmWave V2V Localization in MU-MIMO Hybrid Beamforming

Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in a number of vehicles reduces the Cramr-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters