Investigation of Non-coherent Discrete Target Range Estimation Techniques for High-precision Location

Ranging is an essential and crucial task for radar systems. How to solve the range-detection problem effectively and precisely is massively important. Meanwhile, unambiguity and high resolution are the points of interest as well. Coherent and non-coherent techniques can be applied to achieve range estimation, and both of them have advantages and disadvantages. Coherent estimates offer higher precision but are more vulnerable to noise and clutter and phase wrap errors, particularly in a complex or harsh environment, while the non-coherent approaches are simpler but provide lower precision. With the purpose of mitigating inaccuracy and perturbation in range estimation, miscellaneous techniques are employed to achieve optimally precise detection. Numerous elegant processing solutions stemming from non-coherent estimate are now introduced into the coherent realm, and vice versa. This thesis describes two non-coherent ranging estimate techniques with novel algorithms to mitigate the instinct deficit of non-coherent ranging approaches. One technique is based on peak detection and realised by Kth-order Polynomial Interpolation, while another is based on Z-transform and realised by Most-likelihood Chirp Z-transform. A two-stage approach for the fine ranging estimate is applied to the Discrete Fourier transform domain of both algorithms. An N-point Discrete Fourier transform is implemented to attain a coarse estimation; an accurate process around the point of interest determined in the first stage is conducted. For KPI technique, it interpolates around the peak of Discrete Fourier transform profiles of the chirp signal to achieve accurate interpolation and optimum precision. For Most-likelihood Chirp Z-transform technique, the Chirp Z-transform accurately implements the periodogram where only a narrow band spectrum is processed. Furthermore, the concept of most-likelihood estimator is introduced to combine with Chirp Z-transform to acquire better ranging performance. Cramer-Rao lower bound is presented to evaluate the performance of these two techniques from the perspective of statistical signal processing. Mathematical derivation, simulation modelling, theoretical analysis and experimental validation are conducted to assess technique performance. Further research will be pushed forward to algorithm optimisation and system development of a location system using non-coherent techniques and make a comparison to a coherent approach

Impairments in ground moving target indicator (GMTI) radar

Radars on multiple distributed airborne or ground based moving platforms are of increasing interest, since they can be deployed in close proximity to the event under investigation and thus offer remarkable sensing opportunities. Ground moving target indicator (GMTI) detects and localizes moving targets in the presence of ground clutter and other interference sources. Space-time adaptive processing (STAP) implemented with antenna arrays has been a classical approach to clutter cancellation in airborne radar. One of the challenges with STAP is that the minimum detectable velocity (MDV) of targets is a function of the baseline of the antenna array: the larger the baseline (i.e., the narrower the beam), the lower the MDV. Unfortunately, increasing the baseline of a uniform linear array (ULA) entails a commensurate increase in the number of elements. An alternative approach to increasing the resolution of a radar, is to use a large, but sparse, random array. The proliferation of relatively inexpensive autonomous sensing vehicles, such as unmanned airborne systems, raises the question whether is it possible to carry out GMTI by distributed airborne platforms. A major obstacle to implementing distributed GMTI is the synchronization of autonomous moving sensors. For range processing, GMTI processing relies on synchronized sampling of the signals received at the array, while STAP processing requires time, frequency and phase synchronization for beamforming and interference cancellation. Distributed sensors have independent oscillators, which are naturally not synchronized and are each subject to different stochastic phase drift. Each sensor has its own local oscillator, unlike a traditional array in which all sensors are connected to the same local oscillator. Even when tuned to the same frequency, phase errors between the sensors will develop over time, due to phase instabilities. These phase errors affect a distributed STAP system. In this dissertation, a distributed STAP application in which sensors are moving autonomously is envisioned. The problems of tracking, detection for our proposed architecture are of important. The first part focuses on developing a direct tracking approach to multiple targets by distributed radar sensors. A challenging scenario of a distributed multi-input multi-output (MIMO) radar system (as shown above), in which relatively simple moving sensors send observations to a fusion center where most of the baseband processing is performed, is presented. The sensors are assumed to maintain time synchronization, but are not phase synchronized. The conventional approach to localization by distributed sensors is to estimate intermediate parameters from the received signals, for example time delay or the angle of arrival. Subsequently, these parameters are used to deduce the location and velocity of the target(s). These classical localization techniques are referred to as indirect localization. Recently, new techniques have been developed capable of estimating target location directly from signal measurements, without an intermediate estimation step. The objective is to develop a direct tracking algorithm for multiple moving targets. It is aimed to develop a direct tracking algorithm of targets state parameters using widely distributed moving sensors for multiple moving targets. Potential candidate for the tracker include Extended Kalman Filter. In the second part of the dissertation,the effect of phase noise on space-time adaptive processing in general, and spatial processing in particular is studied. A power law model is assumed for the phase noise. It is shown that a composite model with several terms is required to properly model the phase noise. It is further shown that the phase noise has almost linear trajectories. The effect of phase noise on spatial processing is analyzed. Simulation results illustrate the effect of phase noise on degrading the performance in terms of beam pattern and receiver operating characteristics. A STAP application, in which spatial processing is performed (together with Doppler processing) over a coherent processing interval, is envisioned

OFDM Waveform Optimisation for Joint Communications and Sensing

Radar systems are radios to sense objects in their surrounding environment. These operate at a defined set of frequency ranges. Communication systems are used to transfer information between two points. In the present day, proliferation of mobile devices and the advancement of technology have led to communication systems being ubiquitous. This has made these systems to operate at the frequency bands already used by the radar systems. Thus, the communication signal interferes a radar receiver and vice versa, degrading performance of both systems. Different methods have been proposed to combat this phenomenon. One of the novel topics in this is the RF convergence, where a given bandwidth is used jointly by both systems. A differentiation criterion must be adopted between the two systems so that a receiver is able to separately extract radar and communication signals. The hardware convergence due to the emergence of software-defined radios also motivated a single system be used for both radar and communication. A joint waveform is adopted for both radar and communication systems, as the transmit signal. As orthogonal frequency-division multiplexing (OFDM) waveform is the most prominent in mobile communications, it is selected as the joint waveform. Considering practical cellular communication systems adopting OFDM, there often exist unused subcarriers within OFDM symbols. These can be filled up with arbitrary data to improve the performance of the radar system. This is the approach used, where the filling up is performed through an optimisation algorithm. The filled subcarriers are termed as radar subcarriers while the rest as communication subcarriers, throughout the thesis. The optimisation problem minimises the Cramer--Rao lower bounds of the delay and Doppler estimates made by the radar system subject to a set of constraints. It also outputs the indices of the radar and communication subcarriers within an OFDM symbol, which minimise the lower bounds. The first constraint allocates power between radar and communication subcarriers depending on their subcarrier ratio in an OFDM symbol. The second constraint ensures the peak-to-average power ratio (PAPR) of the joint waveform has an acceptable level of PAPR. The results show that the optimised waveform provides significant improvement in the Cramer--Rao lower bounds compared with the unoptimised waveform. In compensation for this, the power allocated to the communication subcarriers needs to be reduced. Thus, improving the performances of the radar and communication systems are a trade-off. It is also observed that for the minimum lower bounds, radar subcarriers need to be placed at the two edges of an OFDM symbol. Optimisation is also seen to improve the estimation performance of a maximum likelihood estimator, concluding that optimising the subcarriers to minimise a theoretical bound enables to achieve improvement for practical systems

Free-induction-decay magnetometer based on a microfabricated Cs vapor cell

We describe an optically pumped Cs magnetometer containing a 1.5 mm thick microfabricated vapor cell with nitrogen buffer gas operating in a free-induction-decay (FID) configuration. This allows us to monitor the free Larmor precession of the spin coherent Cs atoms by separating the pump and probe phases in the time domain. A single light pulse can sufficiently polarize the atomic sample however, synchronous modulation of the light field actively drives the precession and maximizes the induced spin coherence. Both amplitude and frequency modulation have been implemented with noise floors of 3 pT / √ Hz and 16 pT / √ Hz respectively within the Nyquist limited bandwidth of 500 Hz

GSM based Communication-Sensor (CommSense) System

Using communication signals for radar applications has been a major area of research in radar engineering. In the recent years, due to the widely available wireless signals, a new area of research called commensal radars has emerged. Commensal radars use available wireless Radio Frequency (RF) signals to detect and track targets of interest. This is achieved by placing two antennas, one towards the transmitting base station and the other towards the surveillance area. The signal received by these two antennas are correlated to determine the location and velocity of the target. When a signal passes through a channel, it reflects off the obstacles within its path. These reflections usually degrade quality of the signal and cause interference to the telecommunication systems. To mitigate the effects of the channel on a signal these systems transmit a known bit sequence within each frame. Our goal, with this thesis, is to design and implement a working prototype of a novel architecture for the commensal radar system, which uses these known bit sequences to extract the channel information and determine events of interest. The major novelties of the system are as follows. Firstly, this system will be built upon existing communication systems using Software Defined Radio (SDR) technology. Secondly, this design eliminates the need for a reference antenna, which reduces the cost of the system and creates an opportunity to make the system portable. We name this system Communication-Sensing (CommSense). Since, our plan is to use Global System for Mobile Communication (GSM) as the parent system for the prototype development, we decide to update the name to GSM based Communication-Sensing (GSM-CommSense) system. This thesis begins with theoretical analysis of the feasibility of the GSM-CommSense system. First of all, we perform a link budget analysis to determine the power requirements for the system. Then we calculate the ambiguity function and Cram´er-Rao Lower Bound (CRLB) for a two-path received signal model. With encouraging theoretical results, we design a prototype of the system that can capture real GSM base station broadcast signals. After the design of the GSMCommSense system, we capture channel data from multiple locations with varying environmental conditions. The aim for this set of experiment is to be able to distinguish between different environmental conditions. Then, we performed statistical analysis on the data by means of Probability Density Function (PDF) fitting, a goodness-of-fit test called chi-square test and a clustering algorithm called Principal Components Analysis (PCA). We have presented the results from each analysis and discussed them in detail. Upon, receiving positive results in each step we have decided to move towards using learning algorithms to categorise the data captured by the system. We have compared two widely accepted supervised learning algorithms, called Support Vector Machines (SVM) and Multi-Layer Perceptron (MLP). The results showed that with the current hardware capabilities of the system and the amount of data available per GSM frame, the performance of SVM is better than MLP. Thus, we have used SVM to classify two events of detection and classification across a wall. We have presented our findings and discussed the results in detail. We conclude our current work and provide scope for future work in development and analysis of the GSM-CommSense system

Ultrasensitive 3He magnetometer for measurements of high magnetic fields

We describe a 3He magnetometer capable to measure high magnetic fields (B > 0.1 Tesla) with a relative accuracy of better than 10^-12. Our approach is based on the measurement of the free induction decay of gaseous, nuclear spin polarized 3He following a resonant radio frequency pulse excitation. The measurement sensitivity can be attributed to the long coherent spin precession time T2* being of order minutes which is achieved for spherical sample cells in the regime of motional narrowing where the disturbing influence of field inhomogeneities is strongly suppressed. The 3He gas is spin polarized in-situ using a new, non-standard variant of the metastability exchange optical pumping. We show that miniaturization helps to increase T2* further and that the measurement sensitivity is not significantly affected by temporal field fluctuations of order 10^-4.Comment: 27 pages, 7 figure

Adaptive waveform design for cognitive radar

Advances in technology, especially in sensing, robotics, wireless communications, hardware capabilities and the constant need to confront not only the existing but also new and advanced threats are pushing for the need of advanced radar techniques. In this context, Cognitive Radar (CR) is visualized as the next generation multifunctional, smart and adaptive radar that extends its capabilities and responsibilities far beyond the traditional radar. CR incorporates knowledge gained by the interaction with the environment into its operation therefore forming a closed-loop system aiming to enhance the system performance. A very important element of the CR operation is the ability to adaptively design the transmitted waveforms based on the radar objective and the changes in the environment. In this thesis, we present the different aspects involved in the Cognitive Radar concept with deeper focus on the adaptive waveform design of the system aiming to improve the tracking performance. A method of adaptive waveform design within the sensor management problem ensuring that the total transmitted power is reduced compared to the transmission of a fixed waveform is proposed and finally a promising direction towards the multi-sensor resource allocation and waveform design is presented

A novel array signal processing technique for multipath channel parameter estimation

Cataloged from PDF version of article.Many important application areas such as mobile communication, radar, sonar and remote sensing make use of array signal processing techniques. In this thesis, a new array processing technique called Cross Ambiguity Function - Direction Finding (CAF-DF) is developed. CAF-DF technique estimates direction of arrival (DOA), time delay and Doppler shift corresponding to each impinging signals onto a sensor array in an iterative manner. Starting point of each iteration is CAF computation at the output of each sensor element. Then, using incoherent integration of the computed CAFs, the strongest signal in the delay-Doppler domain is detected and based on the observed phases of the obtained peak across all the sensors, the DOA of the strongest signal is estimated. Having found the DOA, CAF of the coherently integrated sensor outputs is computed to find accurate delay and Doppler estimates for the strongest signal. Then, for each sensor in the array, a copy of the strongest signal that should be observed at that sensor is constucted and eliminated from the sensor output to start the next iteration. Iterations continue until there is no detectable peak on the incoherently integrated CAFs. The proposed technique is compared with a MUSIC based technique on synthetic signals. Moreover, performance of the algorithm is tested on real high-latitude ionospheric data where the existing approaches have limited resolution capability of the signal paths. Based on a wide range of comparisons, it is found that the proposed CAF-DF technique is a strong candidate to define the new standard on challenging array processing applications.Güldoğan, Mehmet BurakM.S

Laser Atmospheric Wind Sounder (LAWS) phase 1. Volume 2

This report summarizes and documents the results of the 12-month phase 1 work effort. The objective of phase 1 was to establish the conceptional definition of the laser atmospheric wind sounder (LAWS) sensor system, including accommodations analyses to ensure compatibility with the Space Station Freedom (SSF) and the Earth Observing System (EOS) Polar Orbiting Platform (POP). Various concepts were investigated with trade studies performed to select the configuration to be carried forward to the phase 2 Preliminary Design Definition. A summary of the LAWS system and subsystem trade studies that were performed leading to the baseline design configuration is presented in the appendix. The overall objective of the LAWS Project is to define, design, and implement an operational space based facility, LAWS, for accurate measurement of Earth wind profiles. Phase 1 addressed three major areas: (1) requirements definition; (2) instrument concepts and configurations; and (3) performance analysis. For the LAWS instrument concepts and configurations, the issues which press the technological state of the art are reliable detector lifetime and laser performance and lifetime. Lag angle compensation, pointing accuracy, satellite navigation, and telescope design are significant technical issues, but they are considered to be currently state of the art. The primary issues for performance analysis concern interaction with the atmosphere in terms of backscatter and attenuation, wind variance, and cloud blockage. The phase 1 tasks were formulated to address these significant technical issues and demonstrate the technical feasibility of the LAWS concept. Primary emphasis was placed on analysis/trade and identification of candidate concepts. Promising configurations were evaluated for performance, sensitivities, risks, and budgetary costs. Lockheed's baseline LAWS configuration is presented