A Survey on Localization for Autonomous Vehicles

Kumar, Debasis; Muhammad, Naveed

doi:10.1109/access.2023.3326069

Cited by 3 publications

(2 citation statements)

References 143 publications

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“…RFID-based wireless sensing is one the core technologies in many fields due to its low cost, labeling ability, easy deployment, and high sensing accuracy, such as indoor scene sensing and positioning [3][4][5], smart agriculture [6][7][8][9], humidity detection [10], trajectory tracking, and attitude recognition [11][12][13]. In the application of metal detection and material sensing [14], especially in localization [15,16], RFID technologies have been developed for many devices due to their low cost and convenient deployment [17]. More recently, the widespread use of these applications in indoor positioning has gradually received much attention from researchers and has generated very meaningful ideas.…”

Section: Introductionmentioning

confidence: 99%

Object Localization and Sensing in Non-Line-of-Sight Using RFID Tag Matrices

Shen,

Duan,

Guo

et al. 2024

Electronics

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RFID-based technology innovated a new field of wireless sensing, which has been applied in posture recognition, object localization, and the other sensing fields. Due to the presence of a Fresnel zone around a magnetic field when the RFID-based system is working, the signal undergoes significant changes when an object moves through two or more different Fresnel zones. Therefore, the moving object can be sensed more easily, and most of the sensing applications required the tag to be attached to the moving object for better sensing, significantly limiting their applications. The existing technologies to detect static objects in agricultural settings are mainly based on X-ray or high-power radar, which are costly and bulky, making them difficult to deploy on a large scale. It is a challenging task to sense a static target without a tag attached in NLOS (non-line-of-sight) detection with low cost. We utilized RFID technologies to sense the static foreign objects in agricultural products, and take metal, rock, rubber, and clod as sensing targets that are common in agriculture. By deploying tag matrices to create a sensing region, we observed the signal variations before and after the appearance of the targets in this sensing region, and determined the targets’ positions and their types. Here, we buried the targets in the media of seedless cotton and wheat, and detected them using a non-contact method. Research has illustrated that, by deploying appropriate tag matrices and adjusting the angle of a single RFID antenna, the matrices’ signals are sensitive to the static targets’ positions and their properties, i.e., matrices’ signals vary with different targets and their positions. Specifically, we achieved a 100% success rate in locating metallic targets, while the success rate for clods was the lowest at 86%. We achieved a 100% recognition rate for the types of all the four objects.

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Section: Introductionmentioning

confidence: 99%

Object Localization and Sensing in Non-Line-of-Sight Using RFID Tag Matrices

Shen,

Duan,

Guo

et al. 2024

Electronics

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show abstract

Section: Introductionmentioning

confidence: 99%

Object localization and recognition using RFID tag matrices in Non-Line-of-Sight

Shen,

Duan,

Guo

et al. 2023

Preprint

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RFID based technology innovated a new field of wireless sensing, which has been applied in posture recognition, object localization and the other sensing fields, the existing sensing methods often require tags to be attached to dynamic targets (because RFID signals are more sensitive to moving target), significantly limiting their applications. It is a challenging task to sensing a static target without tag attached in NLOS (Non-Line-of-Sight). We utilized RFID technologies to sense the static foreign objects in agricultural products, and taken metal, rock, rubber and clod as sensing targets that are common in agricultural. By deploying a tag matrices to create a sensing region, we observed the signal variations before and after the appearance of the targets in this sensing region, determined the targets’ positions and their types. Here, we buried the targets in the media of seedless cotton and wheat, and detected static targets with a non-contact method in the NLOS. Researches illustrated that by deploying appropriate tag matrices and adjusting the angle of a single RFID antenna, the matrices signals can be sensitive to the static targets’ positions and their properties,i.e. matrices signals vary with different targets and their positions. Specifically, we achieved a 100% success rate in locating metallic targets, while the success rate for clods was the lowest at 86%. We achieved a 100% recognition rate for the types of all the four objects.

show abstract