Joint Time-Frequency Signal Processing Scheme in Forward Scattering Radar with a Rotational Transmitter

The feasibility of an X-ray Forward Scatter Radar (FSR) system, which exploits X-ray pulsars as opportunity transmitters, is examined. We provide a power budget estimate for detection of large cosmic objects using such a FSR system and assume the use of the high-resolution X-ray telescopes mounted on a satellite as the receivers. The numerical results are obtained for three types of pulsars and small asteroids, whose diameters equal and overcome 50m.

In this paper we consider a modified sub-optimal signal processing algorithm for marine target detection in a Forward Scatter Radar (FSR) system. The algorithm is based on a matched filtering approach where the filter parameters should be previously estimated. In contrast to the previously developed algorithms, the estimation of target parameters (time, velocity, length) is carried out by means of maximisation of the cross-correlation coefficient between frequencies of the input signal and the reference signal. The algorithm presented in this paper is verified by experimental data, and it can be also applied in some other bistatic radars. (5 pages)

In a forward scatter radar system, the forward scatter shadow ratio to characterize a target is introduced as the ratio of the total received power density to the incident power density for a receiver at a certain location. Numerical simulations show that the forward scatter shadow ratio is related to the size of the target as well as the position of the receiver relative to the target. It is a more suitable parameter for studying target detectability than the radar cross-section.

The forward scatter signature of a target provides the radar systems designer with an alternative approach to the detection of 'very low radar cross section (RCS)' targets. This paper outlines the rationale for a forward scatter radar system, the forward scatter principle, and the architecture of a forward scatter radar systems performance model. This model has been developed to analyse the effect of variations in the choice of operating frequency, transmitter and receiver characteristics, detection and tracking algorithms. The paper discusses these aspects with results from modelling and performance predictions for target forward scatter signature, transmit and receive antenna designs, analogue to digital converter (ADC) performance and coverage for a forward scatter radar system operating in the ultra high frequency (UHF) band.

This paper presents a passive radar system using a signal of opportunity from Digital Video Broadcasting Satellite (DVB-S). The ultimate purpose of the system is to be used as an air traffic monitoring and surveillance system. However, the work focuses on drone detection as a proof of the concept. Detecting a drone by using satellite-based passive radar possess inherent challenges, such as the small radar cross section and low speed. Therefore, this paper proposes a unique method by leveraging the advantage of forward-scattering radar (FSR) topology and characteristics to detect a drone; in other words, the system is known as a passive FSR (p-FSR) system. In the signal-processing algorithm, the empirical mode decomposition (EMD) is applied to the received signal to extract the unique feature vector of the micro-Doppler frequency from the drone’s rotating blades. The paper highlights the p-FSR experimental setup and experiment campaign to detect drones. The experimental results show the feasibility of the p-FSR using a signal transmitted from a satellite to detect flying drone crossing the forward-scatter baseline between the satellite and ground station.

In recent years, the air target detection applications by using GNSS signal have been exploited. In [1-2], the theory of target detection using GPS forward scatter radar was proposed. When the target is near GPS satellite and terrestrial receiver baseline, the detection mode is forward scatterring radar, and the experimental results verify the theory[3]. In [4], the target detection had been implemented based on the shadow, which was formed by the aircraft passing through the GPS satellite and receiver baseline. In [5], different targets are detected by GPS L1 reflected signal power and signal-to-noise ratio, and a signal processing model was proposed which analyzed the target RCS characteristics. The experiment was designed in [7], which was using GPS L5 signal to detect the target successfully. In [8-9], the target detection and the signal processing had been completed by using GPS forward scatterring radar. The classification of objects from their radio shadows of GPS signal was done in [10], which was based on different RCS characteristics of target.

The focus of this paper is on the detection of moving targets with a Forward Scatter Radar system. More precisely, a non-coherent detection strategy is considered and theoretical closed-form expressions of the probability of false alarm and of the probability of detection are derived in order to allow performance prediction and support system design. Finally the theoretical contribution is verified through simulations.

The Tarsier® millimetre wave FMCW radar is a unique system that has been developed by QinetiQ specifically for the detection of unwanted debris on airport runways. The speaker describes the stringent radar requirements, the evaluation of a prototype system and the subsequent full productisation. Examples are shown from the recent installation of four radar units at Vancouver International Airport.

This paper introduces a novel MIMO configuration for Forward Scatter Radar (FSR) systems aimed at extending the capabilities of existing SIMO-based amplitude-only processing methods. Building on prior work, we propose a generalization of the FSR architecture to include both multiple transmit and receive antennas. A key challenge-signal separation among transmitters-is addressed through a frequency division multiplexing (FDM) strategy. We develop a two-dimensional array processing framework that enables joint estimation of Direction of Departure (DOD) and Direction of Arrival (DOA) using amplitude-only data. Both ideal and realistic signal separation scenarios are analyzed, and the resulting processing schemes are derived. Simulations demonstrate the feasibility of the approach and its ability to accurately localize and track targets in the angular domain.

Wireless Sensor Network (WSN) has been emerging in the last decade as a powerful tool for connecting physical and digital world. WSN has been used in many applications such habitat monitoring, building monitoring, smart grid and pipeline monitoring. In addition, few researchers have been experimenting with WSN in many mission-critical applications such as military applications. This paper surveys the literature for experimenting work done in border surveillance and intrusion detection using the technology of WSN. The potential benefits of using WSN in border surveillance are huge; however, up to our knowledge very few attempts of solving many critical issues about this application could be found in the literature.

The wide range of small unmanned aerial vehicles (UAVs) capable of hovering in space, moving at low speeds and at low altitudes, has led to the emergence of a new class of complex radar objects. This, in turn, has led to the development of new radar stations, specifically their main nodes, such as the system for selecting slow-moving targets. Its main purpose is to distinguish moving radar objects (UAVs) against the background of passive interference, such as trees, poles, the earth's surface, hydro and meteorological formations, and so on. This article analyzes research and publications demonstrating the approaches to solving the stated problem. The classical approach to implementing a moving target selection system based on first and second-order digital rejection filters is considered. Its advantages and disadvantages are outlined. New method for combating passive interference in a radar station using the Karhunen-Loève transform, which forms the basis of the principal component analysis data analysis method, is proposed. This method is used to reduce the dimensionality of the data set while retaining maximum energy (information) from the signal reflected from the moving target, while extracting information about stationary objects (data compression). An algorithm for building a moving target selection system for slow-moving targets is provided. The results of the operation of the moving target selection system based on the proposed method and the classical approach are investigated and illustrated. A comparative analysis of the impact of the moving target selection system on the power of the target echo signal is conducted. The dependence of the power of the target echo signal on its speed for the proposed method of selecting moving targets is plotted. Conclusions are drawn regarding the effectiveness of the system for low speeds.

This work proposes the novel use of beacons for precise indoor localization. The proposed (Spinning Indoor Localization) system uses spinning (i.e., rotating) beacons to create and detect predictable and highly distinguishable Doppler signals for sub-meter localization accuracy. The system analyzes Doppler frequency shifts of signals from beacons, which are then used to calculate orientation angles to a target. By obtaining orientation angles from two or more beacons, SpinLoc can precisely locate stationary or slow-moving targets. After designing and implementing the system using MICA2 motes, its performance was tested in an indoor garage environment. The experimental results revealed a median error of 40~50 centimeters and a 90% error of 70~90 centimeters.

The purpose of this paper is to address the capabilities and needs of airborne early warning (AEW) radar. Radar-earth-target geometry, with its associated problems of atmospheric refraction, attenuation, and multipath effects . Relative aircraft-earth-target velocities, with the associated Doppler-processing challenges . Restrictions on frontal area and weight that limit antennas to relatively small sizes, which thereby contribute to poor angular resolution and increased Doppler spreading, complex aircraft/antenna geometry, which contributes to larger antenna sidelobes and distortion of the main lobe . Jamming and other electromagnetic interference. AEW radars use two basic modes of operation: (1) the Doppler mode to detect moving aircraft over land and sea, and (2) the ordinary pulse or non-Doppler mode for detecting stationary or slow-moving targets such as boats or ships. The longrange Doppler detection mode, with its requirements made stringent by operating from a moving platform, distinguishes the AEW radar from others.

Detection of small foreign object debris (FOD) on airport runways is important to prevent accidents. In this study, an FOD detection system that utilizes optically-connected 96 GHz millimeter-wave radar has been developed. This detection system uses Radio-over-Fiber signal transmission between a signal source and several radar antenna units. Further, field evaluations of the developed radar system are carried out at the Tokyo Narita International Airport. The results confirm that the proposed system is capable of detecting objects surrounding the radar antenna. In addition, a 1 inch × 1 inch (diameter × height) metal cylinder is detected with approximately 20 dB signal-to-noise ratio at 450 m.

Airport runway foreign debris (FOD) detection system automatically detects small debris on the airport runway. The primary sensor of the developed FOD detection system is a 90-GHz band millimeter-wave radar. The runway’s clutter could degrade detection performance. In this paper, fundamental aspects of runway clutter are studied at airport tests. Firstly, the radar’s parameters are given. The airport’s measuring conditions are then detailed. The radar cross-section measured is approximately -49 dBsm. In addition, the different clutter characteristics, changed with the center of the runway, are observed due to the runway cross-section gradient.