Detection and Localization of Unmanned Aircraft Systems Using Millimeter-Wave Automotive Radar Sensors

Morris, Peter Joseph Basil; Hari, K.V.S.

doi:10.1109/lsens.2021.3085087

Cited by 31 publications

(11 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Year Application [11] 2010 Autonomous robot navigation [12] 2017 Fluid level sensing [13] 2018 Material classification [14] 2018 Blood glucose level detection [15] 2018 Traffic monitoring [16] 2020 RCS analysis of 9 mm bullet [17] 2021 UAS detection and localization [18] 2022 Vital sign measuring [19] 2022 Blood pressure monitoring [20] 2023 Indoor positioning system…”

Section: Referencementioning

confidence: 99%

See 1 more Smart Citation

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Awan,

Dalveren,

Kara

et al. 2024

Drones

View full text Add to dashboard Cite

Precise altitude data are indispensable for flight navigation, particularly during the autonomous landing of unmanned aerial systems (UASs). Conventional light and barometric sensors employed for altitude estimation are limited by poor visibility and temperature conditions, respectively, whilst global positioning system (GPS) receivers provide the altitude from the mean sea level (MSL) marred with a slow update rate. To cater to the landing safety requirements, UASs necessitate precise altitude information above ground level (AGL) impervious to environmental conditions. Radar altimeters, a mainstay in commercial aviation for at least half a century, realize these requirements through minimum operational performance standards (MOPSs). More recently, the proliferation of 5G technology and interference with the universally allocated band for radar altimeters from 4.2 to 4.4 GHz underscores the necessity to explore novel avenues. Notably, there is no dedicated MOPS tailored for radar altimeters of UASs. To gauge the performance of a radar altimeter offering for UASs, existing MOPSs are the de facto choice. Historically, frequency-modulated continuous wave (FMCW) radars have been extensively used in a broad spectrum of ranging applications including radar altimeters. Modern monolithic millimeter wave (mmWave) automotive radars, albeit designed for automotive applications, also employ FMCW for precise ranging with a cost-effective and compact footprint. Given the technology maturation with excellent size, weight, and power (SWaP) metrics, there is a growing trend in industry and academia to explore their efficacy beyond the realm of the automotive industry. To this end, their feasibility for UAS altimetry remains largely untapped. While the literature on theoretical discourse is prevalent, a specific focus on mmWave radar altimetry is lacking. Moreover, clutter estimation with hardware specifications of a pure look-down mmWave radar is unreported. This article argues the applicability of MOPSs for commercial aviation for adaptation to a UAS use case. The theme of the work is a tutorial based on a simplified mathematical and theoretical discussion on the understanding of performance metrics and inherent intricacies. A systems engineering approach for deriving waveform specifications from operational requirements of a UAS is offered. Lastly, proposed future research directions and insights are included.

show abstract

Section: Referencementioning

confidence: 99%

“…where ∆ f IF is the minimum allowable difference between beat frequencies corresponding to two closely spaced objects at a minimum possible distance, ∆R, away from each other. Modifying (16) accordingly and plugging into (17) gives us the following:…”

Section: Maximum Range and Range Resolutionmentioning

confidence: 99%

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Awan,

Dalveren,

Kara

et al. 2024

Drones

View full text Add to dashboard Cite

show abstract

“…6 To begin, a fundamental tracking architecture has been used in Ref. 7, in which regions of interest are traced in drone frames utilising an ameliorated approach for blob tracing. However, tracing based learning and identification techniques that integrate tracking and identification into a single framework have gained popularity in recent years.…”

Section: Introductionmentioning

confidence: 99%

“…Radars, however, are unable to distinguish between stationary drones and flying birds, and they are also unable to detect hovering drones. 7 In Ref. 8 a revolutionary encryption-based drone identification method was presented to effectively identify an illegal drone.…”

Section: Introductionmentioning

confidence: 99%

Detecting and tracking the position of suspicious objects using vision system

Muthukrishnan,

Kannan,

Prabhu

et al. 2023

Artificial Intelligence for Security and Defence Applications

View full text Add to dashboard Cite

Vision-based object tracking is crucial for both civil and military applications. A range of hazards to cyber safety, vital infrastructure, and public privacy are posed by the rise of drones, or unmanned aerial vehicles (UAV). As a result, identifying suspicious drones/UAV is a serious issue that has attracted attention recently. The key focus of this research is to develop a unique virtual coloured marker based tracking algorithm to recognise and predict the pose of a detected object within the camera field-of-view. After detecting the object, proposed method begins by determining the area of detected object as reference-contour. Following that, a Virtual-Bounding Box (V-BB) is developed over the reference-contour by meeting the minimum area of contour criteria. In order to track and estimate the precise location of the detected object in two-dimensions during observations, a Virtual Dynamic Crossline with a Virtual Static Graph (VDC-VSG) was constructed to follow the motion of V-BB, which is considered as a virtual coloured marker. Additionally, the virtual coloured marker helps to avoid issues linked to ambient lighting and chromatic variation. To some extent, it can function efficiently during obstructions like rapid position fluctuations, low resolution and noises etc. The efficacy of the developed algorithm is evaluated by testing with significant number of aerial sequences, including benchmark footage and the outputs were outstanding, with better results. The suggested method will support future industry of computer vision-based intelligent systems. Potential applications of the proposed method includes object detection and analysis applied to the field of security and defence.

show abstract

“…The indoor human localization and life activity monitoring is proposed in [7]. mmWave radars are explored in several UAV applications [8][9][10][11][12][13][14][15]. However, radars for UAV ground station monitoring and control application is still challenging, as it needs to localize and be able to track the small dynamic UAVs in a wide field of view (theoretically 360 degrees field of view).…”

Section: Introductionmentioning

confidence: 99%

Localization of Multi-Class On-Road and Aerial Targets Using mmWave FMCW Radar

et al. 2021

View full text Add to dashboard Cite

mmWave radars play a vital role in autonomous systems, such as unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), ground station control and monitoring systems. The challenging task when using mmWave radars is to estimate the accurate angle of arrival (AoA) of the targets, due to the limited number of receivers. In this paper, we present a novel AoA estimation technique, using mmWave FMCW radars operating in the frequency range 77–81 GHz by utilizing the mechanical rotation. Rotating the radar also increases the field of view in both azimuth and elevation. The proposed method estimates the AoA of the targets, using only a single transmitter and receiver. The measurements are carried out in a variety of practical scenarios including pedestrians, a car, and an UAV, also known as a drone. With measured data, range-angle maps are created, and morphological operators are used to estimate the AoA of the targets. We also process radar range-angle images for improved visual representation. The proposed method will be extremely beneficial for practical ground stations, traffic control and monitoring frameworks for both on-ground and airborne vehicles.

show abstract

Detection and Localization of Unmanned Aircraft Systems Using Millimeter-Wave Automotive Radar Sensors

Cited by 31 publications

References 11 publications

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Detecting and tracking the position of suspicious objects using vision system

Localization of Multi-Class On-Road and Aerial Targets Using mmWave FMCW Radar

Contact Info

Product

Resources

About