Phase-comparison monopulse radar with switched transmit beams for automotive application

Ohshima, S.; Asano, Yosuke; Harada, Tomohisa; Yamada, Naoyuki; Usui, Mitsuko; Hayashi, Hirotaka; Watanabe, Ryuiku; Iizuka, Hideo

doi:10.1109/mwsym.1999.780235

Cited by 18 publications

(8 citation statements)

References 5 publications

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“…One of the most popular solutions today is based on radar technologies [3], [4]. The radar technology measures reflect-ions from metal objects, and takes into account the Doppler effect in order to provide relative speed information.…”

Section: Intorductionmentioning

confidence: 99%

“…If the alarm is given a few seconds in advance of the collision, many accidents can be prevented [2]. Therefore, while the interests in intelligent vehicles increase, many people have concerns about systems that offer the information of distance and relative speed between two cars.One of the most popular solutions today is based on radar technologies [3], [4]. The radar technology measures reflect-ions from metal objects, and takes into account the Doppler effect in order to provide relative speed information.…”

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confidence: 99%

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Automobile Advance Alarm System Based on Monocular Vision Processing

Lin

Kim

Lin

et al. 2007

2007 International Symposium on Information Technology Convergence (ISITC 2007)

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While the interests in intelligent vehicle increase, many people are having concerns about systems that offer the information of distance and relative speed between two cars. This paper presents an algorithm to obtain efficiently the distance between two cars. IntorductionDriver inattention and poor judgment are the major causes of motor vehicle accidents. Extensive research has shown that intelligent driver assistance systems can significantly reduce the number and severity of these accidents [1]. Compared with vehicles equipped with no crash warning system, vehicles equipped with crash warning systems can reduce more accidents. If the alarm is given a few seconds in advance of the collision, many accidents can be prevented [2]. Therefore, while the interests in intelligent vehicles increase, many people have concerns about systems that offer the information of distance and relative speed between two cars.One of the most popular solutions today is based on radar technologies [3], [4]. The radar technology measures reflect-ions from metal objects, and takes into account the Doppler effect in order to provide relative speed information. However, the high cost of radar systems limits their usefulness.Given that the driving environment is designed around the human driver's ability for visual perception, it may look natural to search for vision solutions. Therefore, another family of solutions is based on image system with two cameras [5], [6]. Such systems are still rather expensive and require accurate calibration between the cameras.The systems based on vision processing with only one camera are recently developed [7-10] and such systems are called "monocular vision system." This paper presents an automobile advance warning algorithm that is carried out using a monocular vision system.Domain limitation via lane identification is proposed in order to efficiently detect advance vehicles. Dark pixel density is used to detect the existence of cars. The distance is calculated using the width between the left and right lanes and the relative speed between two cars is obtained with calculated distance. Finally, the alarm is given a few seconds in advance of the possible collision for drivers to keep safety distance.The proposed algorithm was tested with actual images taken on the road. The 256-gray-level image is used for the simulation. The simulation results show that the maximum error is less than 1 m within the range of 50 m and less than 4 m within the range of 70 m. The simulation results show that more accurate results can be obtained by the proposed algorithm compared with the existing algorithms.The proposed algorithm was implemented using a SoC kit. The included processor is the ALTERA Excalibur ARM EPXAnF1020C3. The image and the calculated distances are displayed via TFT-LCD and a 7-segment, respectively. Figure 1 shows the proposed algorithm for automobile advance alarm systems. Fig.1. Algorithm for automobile advance warning system. This work was supported by the second stage of Brain Korea 21 Project 2007 ...

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Section: Intorductionmentioning

confidence: 99%

mentioning

confidence: 99%

Automobile Advance Alarm System Based on Monocular Vision Processing

Lin

Kim

Lin

et al. 2007

2007 International Symposium on Information Technology Convergence (ISITC 2007)

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“…To find the location, orientation, and motion information of an extended object, it is necessary to both measure the accurate distance from the host vehicle to the object and estimate the boundary positions and pose of the object. To achieve this goal, it is insufficient to use only one available sensing method such as radar [2], [3], mono vision [4], stereo vision [5], [6], or laser radar (ladar) [7].…”

Section: Introductionmentioning

confidence: 99%

Collision Sensing by Stereo Vision and Radar Sensor Fusion

Wu¹,

Decker

Chang³

et al. 2009

IEEE Trans. Intell. Transport. Syst.

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To take advantage of both stereo cameras and radar, this paper proposes a fusion approach to accurately estimate the location, size, pose, and motion information of a threat vehicle with respect to a host one from observations that are obtained by both sensors. To do that, we first fit the contour of a threat vehicle from stereo depth information and find the closest point on the contour from the vision sensor. Then, the fused closest point is obtained by fusing radar observations and the vision closest point. Next, by translating the fitted contour to the fused closest point, the fused contour is obtained. Finally, the fused contour is tracked by using rigid body constraints to estimate the location, size, pose, and motion of the threat vehicle. Experimental results from both synthetic data and real-world road test data demonstrate the success of the proposed algorithm.

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“…These antennas can yield gains in excess of 30 dBi and importantly bandwidths (both radiation and impedance) as broad as the feed element [33]. Figure 7.6.1 shows a photograph of an aperture stacked patch lens coupled antenna, with a bandwidth that covers the entire Ka-band (26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40). Printed reflectarrays are another promising alternative to large 382 arrays of microstrip patches.…”

Section: 6-1 Introductionmentioning

confidence: 99%

“…Such applications include collision avoidance radar [39], high capacity microcellular communication networks [40], Local-Multipoint Distribution Services (LMDS) [41] and simple radio links between Base Station Controllers (BSC) and Base Transceiver Stations (BTS) for present day Personal Communication Systems (peS). Associated with these applications is the need for high gain, low cost and unobtrusive antennas.…”

Section: 6-1 Introductionmentioning

confidence: 99%

Microstrip Patch Arrays

Waterhouse

2003

Microstrip Patch Antennas: A Designer’s Guide

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Phase-comparison monopulse radar with switched transmit beams for automotive application

Cited by 18 publications

References 5 publications

Automobile Advance Alarm System Based on Monocular Vision Processing

Automobile Advance Alarm System Based on Monocular Vision Processing

Collision Sensing by Stereo Vision and Radar Sensor Fusion

Microstrip Patch Arrays

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