FM airborne passive radar

The airborne application of Passive Bistatic Radar (PBR) is the latest evolution of the now established international interest in passive radar techniques. An airborne passive system is cheaper to construct, easier to cool, lighter and requires less power than a traditional active radar system. These properties make it ideal for installation on an Unmanned Aerial Vehicle (UAV), especially for the next generation of Low Observable (LO) UAVs, complementing the platforms LO design with an inherently Low Probability of Intercept (LPI) air-to-air and air-to-ground sensing capability. A comprehensive literature review identified a lack of practical and theoretical research in airborne passive bistatic radar and a quantitative model was designed in order to un- derstand the theoretical performance achievable using a hypothetical system and FM as the illuminator of opportunity. The results demonstrated a useable surveillance volume, assuming conservative estimates for the receiver parameters and allowed the scoping and specification of an airborne demonstrator system. The demonstrator system was subsequently designed and constructed and flown on airborne experiments to collect data for both air-to-air and air-to-ground operation analysis. Subsequent processing demonstrated the successful detection of air targets which correlated with the actual aircraft positions as recorded by a Mode-S/ADS-B receiver. This is the first time this has been conclusively demonstrated in the literature. Doppler Beam Sharpening was used to create a coarse resolution image allowing the normalised bistatic clutter RCS of the stationary surface clutter to be analysed. This is the first time this technique has been applied to an airborne passive system and has yielded the first quantitive values of normalised bistatic clutter RCS at VHF. This successful demonstration of airborne passive radar techniques provides the proof of concept and identifies the key research areas that need to be addressed in order to fully develop this technology

Performance prediction and improvement of a Bistatic Passive coherent location Radar.

Passive Coherent Location (PCL) radar has proved to be feasible in a number of experimental systems, but the lack of comprehensive, published flight trials detracts somewhat from serious consideration of these PCL systems for operational applications, such as Air Traffic Control (ATC). The carrying out of flight trials is, in any case, difficult and very expensive. This dissertation presents a method for accurately predicting the performance of a bistatic passive coherent location radar with the effects of the environment taken into account. The effect of the environement on a propagating electromagnetic wave is obtained from the Advanced Refractive Effects Prediction System (AREPS) model. The resulting performance predictions, in the form of spatial signal-to-noise ratio (SNR), signal-to-interference ratio (SIR) and signal-to-noise-plus-interference ratio (SNIR) maps, provide a powerful planning tool for the application of systems such as ATC. Furthermore, the spatial coverage maps, based on the bistatic radar equation, can be related to a particular probability of detection and false alarm as well as to a required dynamic range of the receiver ADC. Overall, the method provides a visual, as well as a quantitative measure of radar coverage with region-specific atmospheric and terrain effects taken into account. The method proposed in this dissertation offers a marked improvement over traditional performance prediction methods based on the bistatic radar equation within a free space or flat terrain environment. It is understood that the direct path signal of the illuminating transmitter is the cause of some severe limitations within a PCL system. In the interest of suppressing the strong direct signal before the ADC and to complement the development of the prediction method, an antenna pattern was synthesised and applied to an array of folded dipoles in order to place a null in the direction of the strong transmitter. The synthesised antenna pattern and its improvement on the performance of the PCL system was then evaluated using the proposed prediction method presented in this dissertation

Passive bistatic radar based on staring radar illuminators of opportunity.

Passive Bistatic Radar (PBR) systems use non-cooperative illuminators of opportunity to detect, localise and track targets. They have attracted considerable research interest in recent years because they can be operated and deployed at a relatively low cost, they are difficult to detect and hence allow covert operations in hostile environments, and they do not require the allocation of an increasingly more congested frequency spectrum. Various analogue and digital communication systems have been studied and exploited as illuminators of opportunity for PBR in recent years. Despite the extensive work carried out on PBR that exploit random communication signals, there has been limited research investigating the use of existing non-cooperative radar systems as illuminators of opportunity. The exploitation of radar signals to achieve passive bistatic detection is attracting as it may offer significant advantages. Because common radar waveforms are deterministic, a reference channel is essentially not required to detect a target. The knowledge of the deterministic waveform allows the passive receiver to be matched with the illuminator of opportunity and thus generate a Doppler map. Radar signals are also designed for detection and provide a large bandwidth, a good compression ratio and hence enhanced range resolution. The work presented in this thesis investigates PBR solutions that exploit nonrandom signals transmitted by non-cooperative staring radar systems. Staring radar offer a constant illumination of the volume under surveillance and, unlike radar systems that deploy a rotating antenna, offer a continuous signal of opportunity. They are very attractive illuminators in particular for short range applications to detect low-RCS and slow-moving targets, such as drones. In this research, a passive radar prototype, capable of operating with and without a reference channel, was developed and detection performance investigated on data collected in a set of experimental trials with the Thales-Aveillant Gamekeeper staring radar. Results show that moving targets, including drones, could be successfully detected with a PBR exploiting radar signals and operating with and without the reference channel

A scalable real-time processing chain for radar exploiting illuminators of opportunity

Includes bibliographical references.This thesis details the design of a processing chain and system software for a commensal radar system, that is, a radar that makes use of illuminators of opportunity to provide the transmitted waveform. The stages of data acquisition from receiver back-end, direct path interference and clutter suppression, range/Doppler processing and target detection are described and targeted to general purpose commercial off-the-shelf computing hardware. A detailed low level design of such a processing chain for commensal radar which includes both processing stages and processing stage interactions has, to date, not been presented in the Literature. Furthermore, a novel deployment configuration for a networked multi-site FM broadcast band commensal radar system is presented in which the reference and surveillance channels are record at separate locations

Improved Techniques for the Surveillance of the Near Earth Space Environment with the Murchison Widefield Array

In this paper we demonstrate improved techniques to extend coherent processing intervals for passive radar processing, with the Murchison Widefield Array. Specifically, we apply a two stage linear range and Doppler migration compensation by utilising Keystone Formatting and a recent dechirping method. These methods are used to further demonstrate the potential for the surveillance of space with the Murchison Widefield Array using passive radar, by detecting objects orders of magnitude smaller than previous work. This paper also demonstrates how the linear Doppler migration methods can be extended to higher order compensation to further increase potential processing intervals.Comment: Presented at the 2019 IEEE Radar Conference in Boston earlier this yea

The Analysis of Sophisticated Direction of Arrival Estimation Methods in Passive Coherent Locators

In passive coherent locators (PCL) systems, noise and the precision of direction of arrival (DOA) estimation are key issues. This thesis addresses the implementation of sophisticated DOA estimation methods, in particular the multiple signal classification (MUSIC) algorithm, the conventional beam forming (CBF) algorithm, and the algebraic constant modulus algorithm (ACMA). The goal is to compare the ACMA to the MUSIC, and CBF algorithms for application to PCL. The results and analysis presented here support the use of constant modulus information, where available, as an important addition to DOA estimation. The ACMA offers many simple solutions to noise and separation related problems; at low SNR levels, it provides much more accurate estimates and yields reasonable separation performance even in the presence of challenging signals. Differential ACMA, which allows the simple digital removal of the direct signal component from the output of a sensor array, is also introduced

Activity Recognition Based on Micro-Doppler Signature with In-Home Wi-Fi

Device free activity recognition and monitoring has become a promising research area with increasing public interest in pattern of life monitoring and chronic health conditions. This paper proposes a novel framework for inhome Wi-Fi signal-based activity recognition in e-healthcare applications using passive micro-Doppler (m-D) signature classification. The framework includes signal modeling, Doppler extraction and m-D classification. A data collection campaign was designed to verify the framework where six m-D signatures corresponding to typical daily activities are sucessfully detected and classified using our software defined radio (SDR) demo system. Analysis of the data focussed on potential discriminative characteristics, such as maximum Doppler frequency and time duration of activity. Finally, a sparsity induced classifier is applied for adaptting the method in healthcare application scenarios and the results are compared with those from the well-known Support Vector Machine (SVM) method

Passive RF Tomography: Signal Processing and Experimental Validation

Radio frequency (RF) tomography is an imaging technique based upon a set of distributed transmitters and receivers surrounding the area under observation. This method requires prior knowledge of the transmitters\u27 and receivers\u27 locations. In some circumstances the transmitters may be uncooperative, while in other cases extrinsic emitters may be used as source of opportunity. In these scenarios, RF tomography should operate in a passive modality. A previous work postulated the principles and feasibility of passive RF tomography. This research further develops the underlying theory through concise and ad-hoc signal processing. Experimental verification and validation corroborate the effectiveness of passive RF tomography for object detection and imaging

Aircraft state estimation using cameras and passive radar

Multiple target tracking (MTT) is a fundamental task in many application domains. It is a difficult problem to solve in general, so applications make use of domain specific and problem-specific knowledge to approach the problem by solving subtasks separately. This work puts forward a MTT framework (MTTF) which is based on the Bayesian recursive estimator (BRE). The MTTF extends a particle filter (PF) to handle the multiple targets and adds a probabilistic graphical model (PGM) data association stage to compute the mapping from detections to trackers. The MTTF was applied to the problem of passively monitoring airspace. Two applications were built: a passive radar MTT module and a comprehensive visual object tracking (VOT) system. Both applications require a solution to the MTT problem, for which the MTTF was utilized. The VOT system performed well on real data recorded at the University of Cape Town (UCT) as part of this investigation. The system was able to detect and track aircraft flying within the region of interest (ROI). The VOT system consisted of a single camera, an image processing module, the MTTF module and an evaluation module. The world coordinate frame target localization was within ±3.2 km and these results are presented on Google Earth. The image plane target localization has an average reprojection error of ±17.3 pixels. The VOT system achieved an average area under the curve value of 0.77 for all receiver operating characteristic curves. These performance figures are typical over the ±1 hr of video recordings taken from the UCT site. The passive radar application was tested on simulated data. The MTTF module was designed to connect to an existing passive radar system developed by Peralex Electronics Pty Ltd. The MTTF module estimated the number of targets in the scene and localized them within a 2D local world Cartesian coordinate system. The investigations encompass numerous areas of research as well as practical aspects of software engineering and systems design