Polarization techniques for mitigation of low grazing angle sea clutter

Maritime surveillance radars are critical in commerce, transportation, navigation, and defense. However, the sea environment is perhaps the most challenging of natural radar backdrops because maritime radars must contend with electromagnetic backscatter from the sea surface, or sea clutter. Sea clutter poses unique challenges in very low grazing angle geometries, where typical statistical assumptions regarding sea clutter backscatter do not hold. As a result, traditional constant false alarm rate (CFAR) detection schemes may yield a large number of false alarms while objects of interest may be challenging to detect. Solutions posed in the literature to date have been either computationally impractical or lacked robustness. This dissertation explores whether fully polarimetric radar offers a means of enhancing detection performance in low grazing angle sea clutter. To this end, MIT Lincoln Laboratory funded an experimental data collection using a fully polarimetric X-band radar assembled largely from commercial off-the-shelf components. The Point de Chene Dataset, collected on the Atlantic coast of Massachusetts’ Cape Ann in October 2015, comprises multiple sea states, bandwidths, and various objects of opportunity. The dataset also comprises three different polarimetric transmit schemes. In addition to discussing the radar, the dataset, and associated post-processing, this dissertation presents a derivation showing that an established multiple input, multiple output radar technique provides a novel means of simultaneous polarimetric scattering matrix measurement. A novel scheme for polarimetric radar calibration using a single active calibration target is also presented. Subsequent research leveraged this dataset to develop Polarimetric Co-location Layering (PCL), a practical algorithm for mitigation of low grazing angle sea clutter, which is the most significant contribution of this dissertation. PCL routinely achieves a significant reduction in the standard CFAR false alarm rate while maintaining detections on objects of interest. Moreover, PCL is elegant: It exploits fundamental characteristics of both sea clutter and object returns to determine which CFAR detections are due to sea clutter. We demonstrate that PCL is robust across a range of bandwidths, pulse repetition frequencies, and object types. Finally, we show that PCL integrates in parallel into the standard radar signal processing chain without incurring a computational time penalty

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

Mitigation of nonlinear receiver effects in modern radar: advanced signal processing techniques

This thesis presents a study into nonlinearities in the radar receiver and investigates advanced digital signal processing (DSP) techniques capable of mitigating the resultant deleterious effects. The need for these mitigation techniques has become more prevalent as the use of commercial radar sensors has increased rapidly over the last decade. While advancements in low-cost radio frequency (RF) technologies have made mass-produced radar systems more feasible, they also pose a significant risk to the functionality of the sensor. One of the major compromises when employing low-cost commercial off-theshelf (COTS) components in the radar receiver is system linearity. This linearity trade-off leaves the radar susceptible to interfering signals as the RF receiver can now be driven into the weakly nonlinear regime. Radars are not designed to operate in the nonlinear regime as distortion is observed in the radar output if they do. If radars are to maintain operational performance in an RF environment that is becoming increasingly crowded, novel techniques that allow the sensor to operate in the nonlinear regime must be developed. Advanced DSP techniques offer a low-cost low-impact solution to the nonlinear receiver problem in modern radar. While there is very little work published on this topic in the radar literature, inspiration can be taken from the related field of communications where techniques have been successfully employed. It is clear from the communications literature that for any mitigation algorithm to be successful, the mechanisms driving the nonlinear distortion in the receiver must be understood in great detail. Therefore, a behavioural modelling technique capable of capturing both the nonlinear amplitude and phase effects in the radar receiver is presented before any mitigation techniques are studied. Two distinct groups of mitigation algorithms are then developed specifically for radar systems with their performance tested in the medium pulse repetition frequency (MPRF) mode of operation. The first of these is the look-up table (LUT) approach which has the benefit of being mode independent and computationally inexpensive to implement. The limitations of this communications-based technique are discussed with particular emphasis placed on its performance against receiver nonlinearities that exhibit complex nonlinear memory effects. The second group of mitigation algorithms to be developed is the forward modelling technique. While this novel technique is both mode dependent and computationally intensive to implement, it has a unique formalisation that allows it to be extended to include nonlinear memory effects in a well-defined manner. The performance of this forward modelling technique is analysed and discussed in detail. It was shown in this study that nonlinearities generated in the radar receiver can be successfully mitigated using advanced DSP techniques. For this to be the case however, the behaviour of the RF receiver must be characterised to a high degree of accuracy both in the linear and weakly nonlinear regimes. In the case where nonlinear memory effects are significant in the radar receiver, it was shown that memoryless mitigation techniques can become decorrelated drastically reducing their effectiveness. Importantly however, it was demonstrated that the LUT and forward modelling techniques can both be extended to compensate for complex nonlinear memory effects generated in the RF receiver. It was also found that the forward modelling technique dealt with the nonlinear memory effects in a far more robust manner than the LUT approach leading to a superior mitigation performance in the memory rich case

Airborne Radar Interference Suppression Using Adaptive Three-Dimensional Techniques

This research advances adaptive interference suppression techniques for airborne radar, addressing the problem of target detection within severe interference environments characterized by high ground clutter levels, levels, noise jammer infiltration, and strong discrete interferers. Two-dimensional (2D) Space-Time Adaptive Processing (STAP) concepts are extended into three-dimensions (3D) by casting each major 2D STAP research area into a 3D framework. The work first develops an appropriate 3D data model with provisions for range ambiguous clutter returns. Adaptive 3D development begins with two factored approaches, 3D Factored Time-Space (3D-FTS) and Elevation-Joint Domain Localized (Elev-JDL). The 3D adaptive development continues with optimal techniques, i.e., joint domain methods. First, the 3D matched Filter (3D-MF) is derived followed by a 3D Adaptive Matched Filter (3D-AMF) discussion focusing on well-established practical limitations consistent with the 2D case. Finally, a 3D-JDL method is introduced. Proposed 3D Hybrid methods extend current state-of-the-art 2D hybrid methods. The initial 3D hybrid, a functional extension of the 2D technique, exhibits distinct performance advantages in heterogeneous clutter. The final 3D hybrid method is virtually impervious to discrete interference

Advanced Signal Processing For Multi-Mission Airborne Radar

With the technological advancement of the 21st century, functions of different radars are being merged. A multi-functional system brings the technology of remote sensing to a wide array of applications while at the same time reduces costs of implementation and operation. Ground-based multi-mission radars have been studied in the past. The airborne counterpart deserves a through study with additional and stringent requirements of cost, size, weight, and power.In this dissertation, multi-mission functions in an airborne radar is performed using modular, software-based architecture. The software-based solution is chosen instead of proposing new hardware, primarily because evaluation, validation, and certification of new hardware is onerous and time consuming. The system implementations are validated using simulations as well as field measurements. The simulations are carried out using Mathworks® Phased Array System Toolbox. The field measurements are performed using an enhanced commercial airborne radar system called Polarimetric Airborne Radar Operating at X-band Version 1 (PARADOX1), which is an X-band, vertically polarized, solid state, pulsed radar.The shortcomings of PARADOX1 originate from small aperture size and low power. Various signal processing algorithms are developed and applied to PARADOX1 data to enhance the data quality. Super-resolution algorithms in range, angle, and Doppler domains, for example, have proven to effectively enhance the spatial resolution. An end-to-end study of single-polarized weather measurements is performed using PARADOX1 measurements. The results are compared with well established ground-based radars. The similarities, differences as well as limitations (of such comparisons) are discussed. Sense and Avoid (SAA) tracking is considered as a core functionality and presented in the context of safe integration of Unmanned Aerial Vehicles (UAV) in national airspace. A "nearly" constant acceleration motion model is used in conjunction with Kalman Filter and Joint Probabilistic Data Association (JPDA) to perform tracking operations. The basic SAA tracking function is validated through simulations as well as field measurements.The field-validations show that a modular, software-based enhancement to an existing radar system is a viable solution in realizing multi-mission functionalities in an airborne radar. The SAA tracking is validated in ground-based tests using an x86 based PC with a generic Linux operating system. The weather measurements from PARADOX1 and the subsequent data quality enhancements show that PARADOX1 data products are comparable to those of existing ground based radars

Temporal and Spatial Interference Mitigation Strategies to Improve Radar Data Quality

The microwave band is well suited to wireless applications, including radar, communications, and electronic warfare. While radar operations currently have priority in a portion of the microwave band, wireless companies are lobbying to change that; such a change would force current operators into a smaller total bandwidth. Interference would occur, and has already occurred at the former National Weather Radar Testbed Phased Array Radar. The research in this dissertation was motivated by this interference --- it occurred even without a change to radar's primacy in the microwave band. If microwave operations had to squeeze into a smaller overall bandwidth, such interference, whether originating from other radars or some other source, would only become more common. The radio frequency interference (RFI) present at the National Weather Radar Testbed Phased Array Radar altered the statistical properties at certain locations, causing targets to be erroneously detected. While harmless enough in clear air, it could affect National Weather Service decisions if it occurred during a weather event. The initial experiments, covered in Chapter 2, used data comprised of a single channel of in-phase and quadrature (IQ) data, reflecting the resources available to the National Weather Service's weather radar surveillance network. A new algorithm, the Interference Spike Detection Algorithm, was developed with these restrictions in mind. This new algorithm outperforms several interference detection algorithms developed by industry. Tests on this data examined algorithm performance quantitatively, using real and simulated weather data and radio frequency interference. Additionally, machine learning classification algorithms were employed for the first time to the RFI classification problem and it was found that, given enough resources, machine learning had the potential to perform even better than the other temporal algorithms. Subsequent experiments, covered in Chapter 3, used spatial data from phased arrays and looked at methods of interference mitigation that leveraged this spatial data. Specifically, adaptive beamforming techniques could be used to mitigate interference and improve data quality. A variety of adaptive digital beamforming techniques were evaluated in terms of their performance at interference mitigation for a communications task. Additionally, weather radar data contaminated with ground clutter was collected from the sidelobe canceller channels of the former National Weather Radar Testbed Phased Array Radar and, using the reasoning that ground clutter is simply interference from the ground, adaptive digital beamforming was successfully employed to mitigate the impact of ground clutter and restore the data to reflect the statistics of the underlying weather data. Tests on digital equalization, covered in Chapter 4, used data from a prototype receiver for Horus, a digital phased array radar under development at the University of Oklahoma. The data suffered from significant channel mismatch, which can severely negatively impact the performance of phased arrays. Equalization, implemented both via older digital filter design methods and, for the first time, via newer machine learning regression methods, was able to improve channel matching. When used before adaptive digital beamforming, it was found that digital equalization always improved system performance

System Design of Advanced Multi-Beam and Multi-Range Automotive Radar

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2017. 2. 김성철.As the number of vehicles on the road is increased, the incidence of traffic accident is gradually increased and the number of death on roads is also increased. Most accidents are due to carelessness of the driver. If the vehicle can actively recognize the dangerous situation and alert the driver to avoid accident, it will be a great help to the driver. As concern for safety and driver assistance increases, needs for driver assistance system (DAS) are consistently increasing. Moreover, with the grooming demand for autonomous driving, there has been paid a great attention to the incorporation of multiple sensors. Various sensors for safety and convenience are being introduced for automobiles. The detection performance of the automotive radar looks outstanding compared to other sensors such as Lidar, camera, and ultrasonic sensors, in poor weather conditions or environmental conditions of the roads. Among many applications using automotive radars, the adaptive cruise control (ACC) and the autonomous emergency braking (AEB) using forward looking radars are the most basic functions for safety and convenience. Using ACC and AEB functions, drivers can be guaranteed safety as well as convenience when visibility is poor under bad weather conditions. Generally, the radar system for ACC and AEB had been composed of singe longrange radar (LRR) and two of short-range radar (SRR) and the system cost was very expensive. However, the cost can be lowered by the concept of multi-beam, multirange (MBMR) radar which consist of integrated narrow long range beam and wide short range beam in a single radar sensor. In this dissertation, we propose an advanced MBMR radar for ACC and AEB using 77 GHz band and highly integrated RF ICs. The detection specifications are investii gated base on theoretical radar principles and effective design concepts are suggested to satisfy the specifications. We implemented an actually working forward looking MBMR radar and performed experiments to verify the detection performance. To overcome the limitation of radar hardware resources for cost-effective design, we propose novel signal processing schemes to recognize environment on roads which are regarded as impossible with automotive radar. Characteristics of an iron tunnel which deteriorate the detection performance of the radar are analyzed and a measure for the recognition is proposed. Moreover, the recognition method is expanded to harmonic clutters which are caused by man-made structures on roads containing periodic structures such as iron tunnels, guardrails, and sound-proof wall. The harmonic clutter suppression method is also proposed to enhance the quality of the received signal and improve the detection performance of the radar. All experiments are performed using the proposed MBMR radar to verify the detection performance and the usefulness of proposed signal processing methods for recognition and suppression of clutters on roads.1 Introduction 1 2 A Multi-Beam and Multi-Range FMCW Radar using 77 GHz Frequency Band for ACC and AEB 6 2.1 Introduction 6 2.2 System Design of Advanced MBMR Radar 7 2.3 Waveform and Signal Processing Structure Design 14 2.4 Advanced Singal Processing Technique for AEB 19 2.5 Design Results 20 2.6 Experimental Results 22 2.6.1 Anechoic Chamber 22 2.6.2 Field Test 27 2.7 Summary 29 3 Iron-tunnel Recognition 30 3.1 Introduction 30 3.2 Iron-Tunnel Recognition 32 3.2.1 Radar Model 32 3.2.2 Spectral Characteristics of an Iron-Tunnel 34 3.2.3 Measuring Spectrum Spreading 40 3.3 Experimental Result 45 3.3.1 Iron-Tunnel Recognition 45 3.3.2 Early Target Detection and Prevention of Target Drop 49 3.4 Summary 53 4 Clutter Suppression 55 4.1 Introduction 55 4.2 Clutter Recognition 57 4.2.1 Radar Model 57 4.2.2 Spectral Analysis of Road Environment 62 4.2.3 Proposed Clutter-recognition Method (Measuring Harmonics of Clutter) 64 4.3 Clutter Suppression 69 4.3.1 Proposed clutter suppression method 69 4.3.2 Verification using real data 71 4.4 Experimental results 74 4.5 Summary 81 5 Conclusion and Future Works 82 Bilbliography 85 Abstract (In Korean) 89Docto

An investigation of a frequency diverse array

This thesis presents a novel concept for focusing an antenna beam pattern as a function of range, time, and angle. In conventional phased arrays, beam steering is achieved by applying a linear phase progression across the aperture. This thesis shows that by applying an additional linear frequency shift across the elements, a new term is generated which results in a scan angle that varies with range in the far-field. Moreover, the antenna pattern is shown to scan in range and angle as a function of time. These properties result in more flexible beam scan options for phased array antennas than traditional phase shifter implementations. The thesis subsequently goes on to investigate this phenomenon via full scale experimentation, and explores a number of aspects of applying frequency diversity spatially across array antennas. This new form of frequency diverse array may have applications to multipath mitigation, where a radio signal takes two or more routes between the transmitter and receiver due to scattering from natural and man-made objects. Since the interfering signals arrive from more than one direction, the range-dependent and auto-scanning properties of the frequency diverse array beam may be useful to isolate and suppress the interference. The frequency diverse array may also have applications to wideband array steering, in lieu of true time delay solutions which are often used to compensate for linear phase progression with frequency across an array, and to sonar, where the speed of propagation results in large percentage bandwidth, creating similar wideband array effects. The frequency diverse array is also a stepping stone to more sophisticated joint antenna and waveform design for the creation of new radar modes, such as simultaneous multi-mode operation, for example, enabling joint synthetic aperture radar and ground moving target indication

Three Dimensional Bistatic Tomography Using HDTV

The thesis begins with a review of the principles of diffraction and reflection tomography; starting with the analytic solution to the inhomogeneous Helmholtz equation, after linearization by the Born approximation (the weak scatterer solution), and arriving at the Filtered Back Projection (Propagation) method of reconstruction. This is followed by a heuristic derivation more directly couched in the radar imaging context, without the rigor of the general inverse problem solution and more closely resembling an imaging turntable or inverse synthetic aperture radar. The heuristic derivation leads into the concept of the line integral and projections (the Radon Transform), followed by more general geometries where the plane wave approximation is invalid. We proceed next to study of the dependency of reconstruction on the space-frequency trajectory, combining the spatial aperture and waveform. Two and three dimensional apertures, monostatic and bistatic, fully and sparsely sampled and including partial apertures, with controlled waveforms (CW and pulsed, with and without modulation) define the filling of k-space and concomitant reconstruction performance. Theoretical developments in the first half of the thesis are applied to the specific example of bistatic tomographic imaging using High Definition Television (HDTV); the United States version of DVB-T. Modeling of the HDTV waveform using pseudonoise modulation to represent the hybrid 8VSB HDTV scheme and the move-stop-move approximation established the imaging potential, employing an idealized, isotropic 18 scatterer. As the move-stop-move approximation places a limitation on integration time (in cross correlation/pulse compression) due to transmitter/receiver motion, an exact solution for compensation of Doppler distortion is derived. The concept is tested with the assembly and flight test of a bistatic radar system employing software-defined radios (SDR). A three dimensional, bistatic collection aperture, exploiting an elevated commercial HDTV transmitter, is focused to demonstrate the principle. This work, to the best of our knowledge, represents a first in the formation of three dimensional images using bistatically-exploited television transmitters

Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation and Aliasing Artifact Mitigation

Traditional monostatic Synthetic Aperture Radar (SAR) platforms force the user to choose between two image types: larger, low resolution images or smaller, high resolution images. Switching to a Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR) approach allows formation of large high-resolution images. Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. Inverse SAR (ISAR) imagery from a Radar Cross Section (RCS) chamber validates this approach. The second implementation problem stems from the large Doppler spread in the wide-angle scene, leading to severe aliasing problems. This research effort develops a new anti-aliasing technique using randomized Stepped-Frequency (SF) waveforms to form Doppler filter nulls coinciding with aliasing artifact locations. Both simulation and laboratory results demonstrate effective performance, eliminating more than 99% of the aliased energy