Vertical Doppler beam sharpening goes self parking

Laribi, Amir; Hahn, Markus; Dickmann, Jürgen; Waldschmidt, Christian

doi:10.1109/radar.2018.8378589

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…Multi-path radar detections are a well known phenomenon in radar processing. They can be utilized, e.g., to detect objects via reflections beneath a car that occludes the direct path, or for height estimation with conventional 2D radar sensors [3]. Different types of multi-path occurrences are analyzed, e.g.…”

Section: Related Workmentioning

confidence: 99%

Using Machine Learning to Detect Ghost Images in Automotive Radar

Kraus,

Scheiner,

Ritter

et al. 2020

Preprint

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Radar sensors are an important part of driver assistance systems and intelligent vehicles due to their robustness against all kinds of adverse conditions, e.g., fog, snow, rain, or even direct sunlight. This robustness is achieved by a substantially larger wavelength compared to light-based sensors such as cameras or lidars. As a side effect, many surfaces act like mirrors at this wavelength, resulting in unwanted ghost detections. In this article, we present a novel approach to detect these ghost objects by applying data-driven machine learning algorithms. For this purpose, we use a large-scale automotive data set with annotated ghost objects. We show that we can use a state-of-the-art automotive radar classifier in order to detect ghost objects alongside real objects. Furthermore, we are able to reduce the amount of false positive detections caused by ghost images in some settings.

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Section: Related Workmentioning

confidence: 99%

Using Machine Learning to Detect Ghost Images in Automotive Radar

Kraus,

Scheiner,

Ritter

et al. 2020

Preprint

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“…It is a type of imaging radar, often used for ground mapping and clutter discrimination [1]. Whilst it is quite an old technique (dating back to the 1950's), it is now being used in missiles [2], naval radars [3] and in the automotive industry [4], [5]. Missile seekers benefit from using DBS, as it provides a crude imaging capability by improving azimuth resolution without being computationally expensive, like Synthetic Aperture Radars (SAR).…”

Section: Introductionmentioning

confidence: 99%

Deception Jamming Against Doppler Beam Sharpening Radars

2020

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Missile seekers are becoming increasingly more capable of using Doppler Beam Sharpening (DBS) modes as part of the homing cycle, which requires new countermeasures against this mode. One type of countermeasure, is to create false targets within the seeker DBS image. This paper proposes a jamming technique to generate false targets at a precise location within a seeker DBS image, by both delaying and adding a Doppler shift to received waveforms. The effects of tracking errors on the position of the false target are analysed, both analytically and with simulations and used to assess the practical implementation of the jamming scheme. An experimental DBS system was built to test the effectiveness of the jamming scheme against a platform moving in steps and assess errors caused by incorrectly estimating the seeker trajectory. INDEX TERMS Anti-ship missile, DBS, false targets.

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“…The first method uses a multi-path approach to exploit the height information by finding the difference in time delay between the line-of-sight (LoS) component of the signal, and the non-lineof-sight NLoS component [10]. The second method makes use of the Doppler signature of targets and is known as Doppler beam sharpening (DBS) [11], [12]. If the radar platform is moving, and the movement of the platform is known with a high enough precision, then the Doppler information for a target, combined with the azimuthal angular information, can be used to deduce the targets height from the ground.…”

mentioning

confidence: 99%