A Signal Processing Algorithm Based on 2D Matched Filtering for SSAR

This study discusses a smart radar antenna scanning mode that combines features of both the sector-scan mode used for conventional radar and the line-scan mode used for synthetic aperture radar (SAR) and achieves an application of the synthetic aperture technique in the conventional sector-scan (mechanically scanned) radar, and we refer to this mode as sector-scan synthetic aperture radar (SSAR). The mathematical model is presented based on the principle of SSAR, and a signal processing algorithm is proposed based on the idea of two-dimensional (2D) matched filtering. The influences of the line-scan range and speed on the SSAR system are analyzed, and the solution to the problem that the target velocity is very high is given. The performance of the proposed algorithm is evaluated through computer simulations. The simulation results indicate that the proposed signal processing algorithm of SSAR can gather the signal energy of targets, thereby improving the ability to detect dim targets

High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

The challenging potential problems associated with using airborne radar in detection of high Speed Maneuvering Dim Target (HSMDT) are the highly noise, jamming and clutter effects. The problem is not only how to remove clutter and jamming as well as the range migration and Doppler ambiguity estimation problems due to high relative speed between the targets and airborne radar. Some of the recently published works ignored the range migration problems, while the others ignored the Doppler ambiguity estimation. In this paper a new hybrid technique using Optimum Space Time Adaptive Processing (OSTAP), Second Order Keystone Transform (SOKT), and the Improved Fractional Radon Transform (IFrRT) was proposed. The OSTAP was applied as anti-jamming and clutter rejection method, the SOKT corrects the range curvature and part of the range walk, then the IFrRT estimates the target’ radial acceleration and corrects the residual range walk. The simulation demonstrates the validity and effectiveness of the proposed technique, and its advantages over the previous researches by comparing its probability of detection with the traditional methods. The new approach increases the probability of detection, and also overcomes the limitation of Doppler frequency ambiguity

Новый алгоритм оценки вектора скорости цели в РСА на основе согласованного фильтра Меллина

Introduction. Construction of the radar image of a moving target and estimation of its velocity in synthetic aperture radars (SAR) presents a relevant research problem. The low quality of radar imaging is frequently related to the phenomenon of range cell migration (RCM). Conventional methods for RCM compensation, which are successfully used to obtain radar images of stationary targets, fail to provide the required quality when applied to moving targets. At present, a number of algorithms are used to solve this problem. However, the majority of them employ optimization procedures when searching for estimates of unknown parameters, which fact greatly complicates their implementation. An exception is the LvD algorithm, which implements double keystone transform to construct a radar image without using complex estimate search procedures. Radar images are constructed in the coordinates "longitudinal velocity - lateral velocity", which facilitates estimation of the target velocity components.Aim. Development of an alternative algorithm based on the Mellin matched filter (MMF) for estimating the velocity and constructing the radar image of a moving target in a side-looking SAR.Materials and methods. The derived algorithm is based on the invariance of the integral Mellin transform to the signal scale and uses the MMF to estimate the target velocity components.Results. An algorithm for constructing the radar image of a moving target based on the MMF was synthesized. An analysis of the LvD algorithm showed its capacity for selecting the optimum scale factor when implementing a second KT. The conducted computer simulation of the MMF and LvD algorithms showed their equal accuracy. Under the same simulation scenarios, both algorithms yield effective estimates of the velocity components of a moving target when the signal-to-noise ratio is greater than -10 dB.Conclusion. The proposed algorithm for constructing a radar image can be used in SAR systems designed for detection and velocity estimation of a moving target.Введение. Получение радиолокационного изображения (РЛИ) и измерение вектора скорости движущейся цели в радиолокаторах с синтезированной апертурой (РСА) является одной из ключевых задач. Явление миграции сигнала цели по элементам разрешения по дальности является причиной низкого качества РЛИ. Традиционные методы компенсации миграций, которые успешно применяются для получения РЛИ неподвижных объектов, не дают нужного качества в случае применения в обработке сигналов движущейся цели. В настоящее время известны алгоритмы решения поставленной задачи. Однако большинство из них использует оптимизационные процедуры поиска оценок неизвестных параметров, что в значительной степени затрудняет их реализацию. Исключением из этого множества является LvD-алгоритм, который для построения РЛИ использует двукратное применение преобразования "замкового камня". LvD-алгоритм не только не использует сложных процедур поиска оценок, но и позволяет строить РЛИ цели в координатах "продольная скорость - поперечная скорость", что делает задачу оценки составляющих скорости цели чрезвычайно простой. В то же время двукратное применение преобразования "замкового камня", которое использует интерполяцию принятого сигнала, увеличивает нагрузку вычислителя.Цель работы. Разработка альтернативного алгоритма оценки вектора скорости и построения РЛИ движущейся цели в РСА бокового обзора без использования оптимизационных процедур поиска на основе применения согласованного фильтра Меллина (СФМ).Материалы и методы. Полученный алгоритм основан на свойствах инвариантности интегрального преобразования Меллина к масштабу сигнала и использует для оценки составляющих скорости цели согласованный фильтр Меллина.Результаты. В статье приведен синтез алгоритма построения РЛИ движущейся цели, в основании которого лежит применение согласованного фильтра Меллина. Дан анализ LvD-алгоритма, который позволил оптимальным образом выбрать коэффициент масштабирования при реализации KT-преобразования. Проведено математическое моделирование СФМ и LvD-алгоритмов, которое показало их одинаковое качество. Оба алгоритма при одинаковых сценариях моделирования дают эффективные оценки составляющих вектора скорости движущейся цели при отношении сигнал/шум большем -10 дБ.Заключение. Предлагаемый алгоритм построения РЛИ может быть использован при разработке РСА для обнаружения и оценки вектора скорости движущейся цели

A Fast Algorithm of Generalized Radon-Fourier Transform for Weak Maneuvering Target Detection

The generalized Radon-Fourier transform (GRFT) has been proposed to detect radar weak maneuvering targets by realizing coherent integration via jointly searching in motion parameter space. Two main drawbacks of GRFT are the heavy computational burden and the blind speed side lobes (BSSL) which will cause serious false alarms. The BSSL learning-based particle swarm optimization (BPSO) has been proposed before to reduce the computational burden of GRFT and solve the BSSL problem simultaneously. However, the BPSO suffers from an apparent loss in detection performance compared with GRFT. In this paper, a fast implementation algorithm of GRFT using the BSSL learning-based modified wind-driven optimization (BMWDO) is proposed. In the BMWDO, the BSSL learning procedure is also used to deal with the BSSL phenomenon. Besides, the MWDO adjusts the coefficients in WDO with Levy distribution and uniform distribution, and it outperforms PSO in a noisy environment. Compared with BPSO, the proposed method can achieve better detection performance with a similar computational cost. Several numerical experiments are also provided to demonstrate the effectiveness of the proposed method

GNSS-based passive radar techniques for maritime surveillance

The improvement of maritime traffic safety and security is a subject of growing interest, since the traffic is constantly increasing. In fact, a large number of human activities take place in maritime domain, varying from cruise and trading ships up to vessels involved in nefarious activities such as piracy, human smuggling or terrorist actions. The systems based on Automatic Identification System (AIS) transponder cannot cope with non-cooperative or non-equipped vessels that instead can be detected, tracked and identified by means of radar system. In particular, passive bistatic radar (PBR) systems can perform these tasks without a dedicated transmitter, since they exploit illuminators of opportunity as transmitters. The lack of a dedicated transmitter makes such systems low cost and suitable to be employed in areas where active sensors cannot be placed such as, for example, marine protected areas. Innovative solutions based on terrestrial transmitters have been considered in order to increase maritime safety and security, but these kinds of sources cannot guarantee a global coverage, such as in open sea. To overcome this problem, the exploitation of global navigation satellites system (GNSS) as transmitters of opportunity is a prospective solution. The global, reliable and persistent nature of these sources makes them potentially able to guarantee the permanent monitoring of both coastal and open sea areas. To this aim, this thesis addresses the exploitation of Global Navigation Satellite Systems (GNSS) as transmitters of opportunity in passive bistatic radar (PBR) systems for maritime surveillance. The main limitation of this technology is the restricted power budget provided by navigation satellites, which makes it necessary to define innovative moving target detection techniques specifically tailored for the system under consideration. For this reason, this thesis puts forward long integration time techniques able to collect the signal energy over long time intervals (tens of seconds), allowing the retrieval of suitable levels of signal-to-disturbance ratios for detection purposes. The feasibility of this novel application is firstly investigated in a bistatic system configuration. A long integration time moving target detection technique working in bistatic range&Doppler plane is proposed and its effectiveness is proved against synthetic and experimental datasets. Subsequently the exploitation of multiple transmitters for the joint detection and localization of vessels at sea is also investigated. A single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration is proposed. Furthermore, the potential of the system to extract information concerning the detected target characteristics for further target classification is assessed

Computational Algorithms for Improved Synthetic Aperture Radar Image Focusing

High-resolution radar imaging is an area undergoing rapid technological and scientific development. Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) are imaging radars with an ever-increasing number of applications for both civilian and military users. The advancements in phased array radar and digital computing technologies move the trend of this technology towards higher spatial resolution and more advanced imaging modalities. Signal processing algorithm development plays a key role in making full use of these technological developments.In SAR and ISAR imaging, the image reconstruction process is based on using the relative motion between the radar and the scene. An important part of the signal processing chain is the estimation and compensation of this relative motion. The increased spatial resolution and number of receive channels cause the approximations used to derive conventional algorithms for image reconstruction and motion compensation to break down. This leads to limited applicability and performance limitations in non-ideal operating conditions.This thesis presents novel research in the areas of data-driven motion compensation and image reconstruction in non-cooperative ISAR and Multichannel Synthetic Aperture Radar (MSAR) imaging. To overcome the limitations of conventional algorithms, this thesis proposes novel algorithms leading to increased estimation performance and image quality. Because a real-time imaging capability is important in many applications, special emphasis is placed on the computational aspects of the algorithms.For non-cooperative ISAR imaging, the thesis proposes improvements to the range alignment, time window selection, autofocus, time-frequency-based image reconstruction and cross-range scaling procedures. These algorithms are combined into a computationally efficient non-cooperative ISAR imaging algorithm based on mathematical optimization. The improvements are experimentally validated to reduce the computational burden and significantly increase the image quality under complex target motion dynamics.Time domain algorithms offer a non-approximated and general way for image reconstruction in both ISAR and MSAR. Previously, their use has been limited by the available computing power. In this thesis, a contrast optimization approach for time domain ISAR imaging is proposed. The algorithm is demonstrated to produce improved imaging performance under the most challenging motion compensation scenarios. The thesis also presents fast time domain algorithms for MSAR. Numerical simulations confirm that the proposed algorithms offer a reasonable compromise between computational speed and image quality metrics