Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

Advanced signal processing techniques for WiFi-based Passive Radar for short-range surveillance

In this work, advanced signal processing techniques for a Passive Radar (PR) based on WiFi transmissions are considered. The possibility to exploit such a ubiquitous and accessible source is shown to be an appropriate choice for the detection, localization and imaging of vehicles, people and aircrafts within short ranges in both outdoor and indoor environments

Indoor Ground Testing of a Small UAS Sense and Avoid Airborne Doppler Radar

The National Aeronautics and Space Administrations Unmanned Aircraft System (UAS) Traffic Management (UTM) project is researching prototype technologies needed to ensure safe integration of UAS operations into the National Airspace System (NAS). Within the UTM Concept of Operations, UAS would be equipped with on-board Sense and Avoid (SAA) technology to continually monitor for manned and unmanned aircraft in its vicinity while operating beyond visual line of sight in uncontrolled airspace. To support this effort, a candidate commercially available 24.5 GHz Doppler radar was selected and evaluated to determine if the technology could reliably support minimum requirements for SAA applications of small UAS (sUAS). Indoor ground tests were conducted inside the NASA Langley Research Centers Experimental Test Range (ETR) from a stationary platform to evaluate the Doppler radar performance characteristics and gain operational proficiency before the radar was authorized to transmit outdoors. A high speed linear rail system was developed for the radar evaluation and was shown to be an effective method to generate Doppler radar targets of known radar cross section. The accuracy of the range and velocity reported by the radar was shown to be dependent on the Kalman filter state variance parameter settings. Antenna measurements were collected with the radar installed both on and off a sUAS to quantify the relative antenna gain, beam width and side lobe levels of the radars Metamaterial Electronically Scanning Array (MESA) antennas at boresight and extreme field of view pointing vectors. The relative antenna gain measured 2.6 dB lower at extreme field view angles compared to the boresight radiation pattern

Beware the Boojum: Caveats and Strengths of Avian Radar

Radar provides a useful and powerful tool to wildlife biologists and ornithologists. However, radar also has the potential for errors on a scale not previously possible. In this paper, we focus on the strengths and limitations of avian surveillance radars that use marine radar front-ends integrated with digital radar processors to provide 360° of coverage. Modern digital radar processors automatically extract target information, including such various target attributes as location, speed, heading, intensity, and radar cross-section (size) as functions of time. Such data can be stored indefinitely, providing a rich resource for ornithologists and wildlife managers. Interpreting these attributes in view of the sensor’s characteristics from which they are generated is the key to correctly deriving and exploiting application-specific information about birds and bats. We also discuss (1) weather radars and air-traffic control surveillance radars that could be used to monitor birds on larger, coarser spatial scales; (2) other nonsurveillance radar configurations, such as vertically scanning radars used for vertical profiling of birds along a particular corridor; and (3) Doppler, single-target tracking radars used for extracting radial velocity and wing-beat frequency information from individual birds for species identification purposes

A Review of Automatic Classification of Drones Using Radar:Key Considerations, Performance Evaluation and Prospects

Automatic target classification or recognition is a critical capability in non-cooperative surveillance with radar in several defence and civilian applications. It is a well-established research field and numerous techniques exist for recognising targets, including miniature unmanned air systems or drones (i.e., small, mini, micro and nano platforms), from their radar signatures. These algorithms have notably benefited from advances in machine learning (e.g., deep neural networks) and are increasingly able to achieve remarkably high accuracies. Such classification results are often captured by standard, generic, object recognition metrics and originate from testing on simulated or real radar measurements of drones under high signal to noise ratios. Hence, it is difficult to assess and benchmark the performance of different classifiers under realistic operational conditions. In this paper, we first review the key challenges and considerations associated with the automatic classification of miniature drones from radar data. We then present a set of important performance measures, from an end-user perspective. These are relevant to typical drone surveillance system requirements and constraints. Selected examples from real radar observations are shown for illustration. We also outline here various emerging approaches and future directions that can produce more robust drone classifiers for radar

Radar Range Deception with Time-Modulated Scatterers

Modern radar systems are designed to have high Doppler tolerance to detect fast-moving targets. This means range and Doppler estimations are inevitably coupled, opening pathways to concealing objects by imprinting artificial Doppler signatures on the reflected echoes. Proper temporal control of the backscattered phase can cause the investigating radar to estimate wrong range and velocity, thus cloaking the real position and trajectory of the scatterer. This deception method is exploited here theoretically for arbitrary Doppler tolerant waveforms and then tested experimentally on an example of the linear frequency modulated radar, which is the most common waveform of that class used in practice. The method allows retaining radio silence with a semi passive (battery assisted) approach that can work well with time-dependent metasurfaces. Furthermore, as an insight into new capabilities, we demonstrate that temporally concealed objects could even be made to appear closer than they truly are without violating the laws of relativity

A test methodology for the validation of Doppler video instrumentation for fighter aircraft radar in development of electronic protection

There is a need to measure the effects of radar jamming on modern military radar systems. An advanced Doppler video system designed to measure the effects of jammers on radar systems was developed by the United States Air Force Electronic Warfare Division. This thesis develops a methodology that can be used to effectively validate such an instrumentation system. The Doppler video instrumentation system was an advanced system geared specifically towards developing counter-jamming techniques by capturing the raw RF data entering the radarThe methodology developed was a process of sequenced tests designed to evaluate the Doppler video instrumentation system. Applications into the development of electronic counter-countermeasures are described to illustrate the processes required by this methodology. The typical radar instrumentation connects only to the radar processor, recording the various operating modes or calculated range and closing rates of targets, and does not capture the RF spectrum. That type of system is easily validated through the comparison of radar processor data to target tracking data from a surveyed ground radar or other truth source. The challenge of validating the Doppler video instrumentation was in selecting specific tests to determine the accuracy of the frequency and intensity measurements of the RF spectrum. The methodology used a building block approach, starting with ground tests and advancing to flight tests. Ground-testing involved direct injection of a signal into the radar, exercising the full range of bandwidth and intensity. Flight testing assessed radar baseline performance to determine the impact of the instrumentation system\u27s insertion loss on detection and lock-on range. Flight testing included examining the effects of Doppler shifts and frequency roll-off at radar gimbal. Flight tests against a target equipped with a programmable radar jammer were designed to evaluate performance against techniques such as noise, range gate pull-off and velocity gate pull-off. The methodology demonstrated that the Doppler video instrumentation system met the accuracy requirements for monitoring the frequency and intensity data from the radar under test in both ground and flight phases. Flight testing also successfully assessed the capability of the instrumentation system to capture jamming techniquesThe radar under test was observed in jamming runs to apply an attenuating filter to manage the power levels for the receiver and in the process lose the faint skin returnAdditional testing in an anechoic chamber or with a calibrated airborne signal collector was recommended to enhance the measurement of intensity error

Electromagnetic guidance study

Electromagnetic sensors for guidance and control during spacecraft dockin

Pattern-theoretic foundations of automatic target recognition in clutter

Issued as final reportAir Force Office of Scientific Research (U.S.