Raytheon Technologies (Canada)

An integrated maritime surveillance (IMS) system, based on high-frequency surface-wave radars (HFSWR), is described. IMS provides low-cost, 24-hour, real-time, over-the-horizon surveillance of large ocean areas, out to the 200 nautical mile Exclusive Economic Zone (EEZ). The system can be used to coordinate search and rescue operations, and to combat smuggling, drug trafficking, illegal dumping of pollutants, and other undesirable activities. The major challenges in using HFSWR are (i) operating within the crowded HF spectrum; and (ii) maintaining effective operation in high environmental noise, ocean clutter, ionospheric clutter and other undesirable sources of interferences. The system is outlined and these problems are addressed. Numerical simulation, as well as stochastic modeling, are presented to demonstrate the physics behind the system.

High-level information fusion (situation and threat assessment, process and user refinement) requires novel solutions for the operational transition of information fusion designs. Low-level (signal processing, object state estimation and characterization) is well-vetted in the community as compared to high-level information fusion (control and relationships to the environment). Specific areas of interest include modeling (situations, environments), representations (semantic, knowledge, and complex), information management (ontologies, protocols) systems design (scenario-based, user-based, distributed-agent) and evaluation (measures of performance/effectiveness, and empirical case studies).

For pt.1 see ibid., vol.43, no.4, p.28-43 (2001). An integrated maritime surveillance (IMS) system, based on high-frequency surface wave radars (HFSWR), for monitoring surface and low-level air activity within the 200 nautical mile (nm) Exclusive Economic Zone (EEZ) is described in this two-part paper. The science behind the long-range performance of HFSWR was presented in Part 1(Sevgi et al. 2001). The system described was installed on Canada's east coast, where it is being used to demonstrate continuous, all-weather surveillance of the EEZ to beyond 200 nm. The system consists of two land-based HFSWRs and an operations control center (OCC). The two unmanned radars provide coverage of the Grand Banks region of Newfoundland, renowned for its offshore resources, particularly fish and oil. The system has been designed to assist authorities to more efficiently monitor such illegal activities as drug trafficking, smuggling, piracy, illicit fishing and illegal immigration. In addition, the system may be used for tracking icebergs, environmental protection, search and rescue, resource protection, sovereignty monitoring, and remote sensing of ocean surface currents and winds. Extensive performance testing of the system has been conducted using the two fully functional radars. It is shown that the HFSWR system complements existing surveillance assets to dramatically increase the effectiveness of air and surface reconnaissance missions by vectoring them directly to targets of interest.

With the rapidly growing use of commercial Unmanned Aerial Vehicles (UAVs), integrating civilian UAVs into the controlled airspace seems inevitable. We investigate the problem of associating correct labels to different radar tracks, specifically to distinguish UAV tracks among others (such as aircraft and birds). To this end, three plausible civilian applications involving UAVs are proposed and studied. Then, for each application, a number of UAV tracks are simulated and merged into an existing dataset of real aircraft and bird tracks. We show that, with a chosen set of track features, the simulated UAV tracks are correctly labeled with 99% accuracy.

In multitarget tracking, in addition to the problem of measurement-to-track association, there are decision problems related to track confirmation and termination. In general, such decisions are taken based on the total number of measurement associations, length of no association sequence, and total lifetime of the track in question. For a better utilization of available information, confidence of the tracker on a particular track can be used. This quantity can be computed using the measurement-to-track association likelihoods corresponding to the particular track, target detection probability for the sensor-target geometry, and false alarm density. A track quality measure is proposed here for assignment-based global nearest neighbor (GNN) trackers. It can be noted that to compute track quality measure for assignment-based data association one needs to consider different detection events than those considered for computation of the track quality measures available in the literature, which are designed for probabilistic data association (PDA) based trackers. In addition to the proposed track quality measure, a multitarget tracker based on it is developed, which is particularly suitable in scenarios with temporarily undetectable targets. In this work, tracks are divided into three sets based on their quality and measurement association history: initial tracks, confirmed tracks, and unobservable tracks. Details of the update procedures of the three track sets are provided. The results show that discriminating tracks on the basis of their track quality can lead to longer track life while decreasing the average false track length.

We describe a novel modular learning strategy for the detection of a target signal of interest in a nonstationary environment, which is motivated by the information preservation rule. The strategy makes no assumptions on the environment. It incorporates three functional blocks: (1) time-frequency analysis, (2) feature extraction, and (3) pattern classification, the delineations of which are guided by the information preservation rule. The time-frequency analysis, which is implemented using the Wigner-Ville distribution (WVD), transforms the incoming received signal into a time-frequency image that accounts for the time-varying nature of the received signal's spectral content. This image provides a common input to a pair of channels, one of which is adaptively matched to the interference acting alone, and the other is adaptively matched to the target signal plus interference. Each channel of the receiver consists of a principal components analyzer (for feature extraction) followed by a multilayer perceptron (for feature classification), which are implemented using self-organized and supervised forms of learning in feedforward neural networks, respectively. Experimental results based on real-life radar data are presented to demonstrate the superior performance of the new detection strategy over a conventional detector using constant false-alarm rate (CFAR) processing. The data used in the experiment pertain to an ocean environment, representing radar returns from small ice targets buried in sea clutter; they were collected with an instrument quality coherent radar and properly ground truthed.

In today's resource-driven economy, maritime nations are claiming economic borders that extend beyond the continental shelf or the 200 nautical mile (nm) Exclusive Economic Zone (EEZ). However, claiming such large economic area places responsibilities on the parent nation to exercise jurisdiction through surveillance and enforcement. The requirement to see beyond the horizon has long been a goal of maritime security forces. Today, this is largely dependent on cooperative vessels voluntarily communicating their intentions to local shore-side authorities, as well as on those vessel sightings reported by patrollers. Recent advances in technology provide maritime nations with options to provide more systematic surveillance of both cooperative and non-cooperative targets. This paper presents an overview of a land-based High Frequency Surface Wave Radar (HFSWR) used to provide persistent, active, surveillance. The paper demonstrates that these radars have now reached a level of maturity where their performance is predictable and that they can, within known limits, reliably detect and track ocean going vessels throughout the EEZ.

Abstract Nanobubble (NB) technology has advanced significantly over the last two decades. Many theoretical and technological advances have been made, including the development of novel devices for NB generation. Proof of principle has been demonstrated primarily at laboratory scale and very encouraging results have been obtained. Yet reports on applications in the field (for ecosystem restoration) or at industrial or large pilot scale (for wastewater treatment) are lacking. In this paper, five field applications of an industrial strength nanobubble generator are presented and key environmental quality parameters have been measured and are presented here. The results indicate the highly successful application of NB technology; however, in most cases the lack of benchmarking does not allow for a quantitative comparison of the benefits of this technology. However, the presented results provide convincing evidence that NB technology works beyond the bench scale in the field and in industrial testing trials. For example, a 1600 m 3 winery wastewater pond was fully restored in 10 weeks and the energy required for COD removal was estimated at 0.515 kWh/kg‐COD. The presented results are a strong indicator of the potential success of the NB technology in environmental applications.

Abnormal fluctuations have been observed in detected power levels of some of the targets during trials of the integrated maritime surveillance system (IMS) based on the Canadian east coast surface-wave high-frequency radar (HFSWR). The power level of most of the surface and air targets fluctuated within measurement-error limits (a few dB) during consecutive detections. These fluctuations have been observed to be more than 15 dB for a huge oil platform and nearby large tankers. These fluctuations are quite different than those observed in microwave radars, such as pulse-to-pulse or scan-to-scan fluctuations (which are modeled as different Swerling-type targets), and as are mentioned in most of the classical radar handbooks. In order to understand the reason behind these fluctuations, the behavior of the target reflectivity and radar cross section (RCS) of surface and air targets and their mutual RCS interaction were investigated. Powerful numerical techniques were used to model and understand the target reflectivity and RCS interactions, mostly in the resonance regime. Different scenarios were created, and the mutual RCS behavior of nearby large targets (such as oil tankers and/or fixed offshore oil platforms) as they were maneuvering were modeled. It was shown that 10 dB to 20 dB RCS fluctuations should be expected when targets interact, especially in the resonance regime.

This work studies zero-feedback distributed beamforming; we are motivated by scenarios where the links between destination and all distributed transmitters are weak, so that no reliable communication in the form of pilot signals or feedback messages can be assumed. Furthermore, we make the problem even more challenging by assuming no specialized software/hardware for distributed carrier synchronization; we are motivated by ultra-low complexity transceivers. It is found that zero-feedback (i.e. blind), constructive, distributed signal alignment at the destination is possible; the proposed scheme exploits lack of carrier synchronization among M distributed transmitters and provides beamforming gains. Possible applications include reachback communication in low-cost sensor networks with simple (i.e. conventional, no carrier frequency/phase adjustment capability) radio transceivers.

In the past decade many countries have launched programs to deploy wind turbines as alternative sources of electrical energy. When deployed in wind farms this technology has raised concerns from both air traffic control (ATC) and military authorities. This is due to the fact that the turbine blades return radar echoes that have the potential to distract and confuse the air traffic picture by creating false detections that can effectively mask genuine aircraft returns. Most of the mitigation solutions offered today are either primarily based on such measures as range-azimuth gating or inhibiting track initiation in the vicinity of wind farms. These draconian measures can result in a significant degradation in radar performance and potential air traffic control disruption. They may also require costly redesign of the existing radars. This paper presents a set of 'clean' solutions that mitigate, and in some cases completely eliminate the effect of wind turbine returns. The solution is based on the combination of discrimination techniques applied at the pre-detection, detection and post detection stages of the radar signal processing chain. The suit of mitigation solutions developed does not adversely affect aircraft detection, and can be readily retrofitted to the existing ATC primary surveillance radars (PSR).

A modified Cramer-Rao bound is derived that takes account of the fact that the symbol timing estimate is restricted to a finite interval of one symbol duration. A detection theory bound is also applied to the symbol timing problem. Results obtained using the Cramer-Rao and detection theory bounds are compared. It is shown that the detection theory bound is superior to the traditionally used Cramer-Rao bound. In particular, the detection theory bound gives useful results for sharp pulse shapes and shows a dependence of the mean square error on the data sequence. It also yields meaningful results for small signal-to-noise ratios.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The concept of instantaneous parameters, which has previously been associated exclusively with 1-D measures like the instantaneous frequency and the group delay, are extended to the 2-D time-frequency plane. Such generalized instantaneous parameters are associated with the short-time Fourier transform. They may also be interpreted as local moments of certain time-frequency distributions. It is shown that these measures enable local signal behavior to be characterized in the time-frequency plane for nonstationary deterministic signals. The usefulness of the generalized instantaneous parameters is demonstrated in their application to optimal selection of windows for spectrograms. This is achieved through window matching in the time-frequency plane. An algorithm is provided that illustrates the performance of this window matching. Results based on simulated and real data are presented.

Abstract The applications of advanced ceramics, composites and coatings in mineral, mining, fuel production, and processing are reviewed. The materials include oxide and non‐oxide ceramics (specifically SiC‐based), ceramic–ceramic, and ceramic–metal composites, coatings on metallic components where functional application properties can be achieved. Some principles of materials selection, specifically for erosion wear and corrosion applications, and manufacturing are considered. The examples of the successful development and processing of ceramics, coatings, and composites with manageable structures and phase compositions, in the erosion‐related applications, particularly conducted by the author, are discussed and reviewed. Specifically, industrially employed types of ceramics and processing routes were focused on the considered applications. Particular demands for advanced materials with high reliability and complex shapes or for protective coatings on complex shape steel components and long tubing with inner surface protection require novel and optimized processing. The factors affecting erosion and erosion–corrosion resistance and the paths for the erosion resistance enhancement of ceramic and coating materials are considered. Ceramic components design, technology, and installation features are reviewed.

A technique that performs better than conventional, noncoherent marine radars in detecting small pieces of glacial ice (growlers) in the sea is reported. A coherent detector based on an autoregressive (AR) parameterization of received radar echoes that distinguishes growler returns from the background sea clutter returns is considered. A conventional noncoherent detector is also evaluated as a basis for comparison. The AR-based detector is shown to offer significant improvements in detecting growlers. The results reported are based on real X-band radar data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

In this paper, we derive a time-varying model for the steering vector of a phased array pulse Doppler radar system installed on a moving platform. Six oscillating motions are included in the derived model as well as the forward motion of the platform. We also present the sensitivity analysis of the derived model and analyze the effect of the perturbation between the true and measured array manifold on the accuracy of the motion compensation algorithm. From the simulation, it can be shown that the platform motions have no prominent effects on the target's power spectrum in moderate sea states (up to 3). However the barge's forward motion is a problem if the targets fall in the spreading spectral region of the sea clutter.

The aim of this paper is to identify false tracks that arise from weather and biological targets, and to increase the air traffic security and safety level by detecting aircrafts lacking secondary surveillance radar (SSR) data. In this paper a single-source target classification after tracking using support vector machines (SVM) is introduced, which gives each track an updated probability value based on its likelihood behavior to conform to aircraft and non-aircraft targets. We introduce various features and evaluate different combinations in order to achieve the highest clustering index. The experimental classification results with real radar data provide good evidence that machine target classification is viable, with the capability of being implemented in real time.

The author discusses the foundation principles of iterative software development. He goes on to examine a set of heuristics that he has found useful when applying iterative development methods to define the contents of subsequent increments. Understanding the heuristics helps provide vision and focus, which is essential when building complex systems. All the examples share the same domain, that of an advanced air traffic control (ATC) system, admittedly simplified to illustrate the points for an audience that might not be familiar with the ATC domain. The choice is not accidental. Designers successfully used incremental development, and the heuristics described, to build the Canadian Automated Air Traffic System, probably the most advanced system of its kind.

In multitarget tracking alongside the problem of measurement to track association, there are decision problems related to track confirmation and termination. In general, such decisions are taken based on the total number of measurement associations, length of no association sequence, total lifetime of the track in question. For a better utilization of available information, confidence of the tracker on a particular track can be used. This quantity can be computed from the measurement-to-track association likelihoods corresponding to the particular track, target detection probability for the sensor-target geometry and false alarm density. In this work we propose a multitarget tracker based on a track quality measure which uses assignment based data association algorithm. The derivation of the track quality is provided. It can be noted that in this case one needs to consider different detection events than that of the track quality measures available in the literature for probabilistic data association (PDA) based trackers. Based on their quality and length of no association sequence tracks are divided into three sets, which are updated separately. The results show that discriminating tracks on the basis of their track quality can lead to longer track life while decreasing the average false track length.

Multi- <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">h</tex> schemes are bandwidth-efficient CPM signaling formats which offer means of coding without explicit redundancy. However, the required (optimal) receiver structures tend to be very complex [1], [4], [8] requiring a large number of filters of correlators. Here a reduced complexity receiver for the joint estimation of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</tex> -ary data, carrier phase, and symbol timing is realized through the use of an approximate representation of the likelihood function. Evaluation of receiver performance indicates a fraction of a decibel degradation in coding gain and almost no loss in synchronization performance.