Angle-of-arrival assisted Radio Interferometry (ARI) target localization

Friedman, Jonathan; Charbiwala, Zainul; Schmid, Thomas; Cho, Young; Srivastava, Mani

doi:10.1109/milcom.2008.4753068

Cited by 22 publications

(14 citation statements)

References 7 publications

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“…There has been significant work on Wi-Fi device localization [8,53] using techniques including RSSI [15,48] and fine-grained channel state information [44]. The state of the art systems [7,21,51] achieve sub-meter localization accuracies using statistical angle-of-arrival techniques such as MUSIC [43]. More recently work on motion detection [38,19,28,14,42,46] uses changes to the wireless signals caused by human motion such as running [14], walking forward and backward [19], body gestures [38,28], and activity recognition [42,46].…”

Section: Related Workmentioning

confidence: 99%

Feasibility and limits of wi-fi imaging

Huang

Nandakumar

Gollakota

2014

Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems

141

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We explore the feasibility of achieving computational imaging using Wi-Fi signals. To achieve this, we leverage multi-path propagation that results in wireless signals bouncing off of objects before arriving at the receiver. These reflections effectively light up the objects, which we use to perform imaging. Our algorithms separate the multi-path reflections from different objects into an image. They can also extract depth information where objects in the same direction, but at different distances to the receiver, can be identified. We implement a prototype wireless receiver using USRPN210s at 2.4 GHz and demonstrate that it can image objects such as leather couches and metallic shapes in line-of-sight and non-line-of-sight scenarios. We also demonstrate proofof-concept applications including localization of static humans and objects, without the need for tagging them with RF devices. Our results show that we can localize static human subjects and metallic objects with a median accuracy of 26 and 15 cm respectively. Finally, we discuss the limits of our Wi-Fi based approach to imaging.

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Section: Related Workmentioning

confidence: 99%

Feasibility and limits of wi-fi imaging

Huang

Nandakumar

Gollakota

2014

Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems

141

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“…The angle-of-arrival (AOA) method [45], [46], [47], [36] involves determining the angular separation between two beacons, or a single beacon and a fixed axis. By determining the AOA at a certain number of sensor nodes, position can be determined by angulation methods, as outlined in Section 3.3.…”

Section: Measurement Phasementioning

confidence: 99%

A Survey on Localization for Mobile Wireless Sensor Networks

Amundson

Koutsoukos

2009

Mobile Entity Localization and Tracking in GPS-less Environnments

246

140

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Abstract. Over the past decade we have witnessed the evolution of wireless sensor networks, with advancements in hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been much focus on mobile sensor networks, and we have even seen the development of small-profile sensing devices that are able to control their own movement. Although it has been shown that mobility alleviates several issues relating to sensor network coverage and connectivity, many challenges remain. Among these, the need for position estimation is perhaps the most important. Not only is localization required to understand sensor data in a spatial context, but also for navigation, a key feature of mobile sensors. In this paper, we present a survey on localization methods for mobile wireless sensor networks. We provide taxonomies for mobile wireless sensors and localization, including common architectures, measurement techniques, and localization algorithms. We conclude with a description of real-world mobile sensor applications that require position estimation.

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“…Therefore, range-free localization procedure is not optimal. Ranging approaches such as RSSI [10], [11], [12], Angle of Arrival (AOA) [13], [14], Time Difference of Arrival (TDOA) [15], [16], Time of arrival (TOA) [17], Lighthouse [18], Ultra wideband (UWB) [19], and other schemes have been widely used in a variety of ranging fields including in Wifi but not yet in WiMax domain. Each of these approaches has its own advantage sand disadvantages.…”

Section: Introduction 11background Of Studymentioning

confidence: 99%

Analysis of Addax-Sinopec Outdoor Pathloss Behavior for WiFi and WiMAX Infrastructure

Ezeh¹,

Nwogu²,

Okafor³

2016

IJCA

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In wireless environments, improper handover among mobile terminals can occur during micromobility due to various reasons. Once this takes place, the network Quality of Service (QoS) experiences degradation thereby increasing the call drop rate, creating latency problems and decreasing throughput. In such scenario, there is an urgent need to optimize network performance while utilizing network resources efficiently. Interestingly, various pathloss methods have been recently proposed to achieve relative network performance but these methods have high complexity and are cost effective. This work applied Hata model in spatial micromobility environment to evaluate the performance of mobile wireless access within Wifi and WiMax infrastructures. The work used Addax-Sinopec petroleum, a drilled deep exploratory oil well in Izombe, Oguta Local Government area situated in the south eastern part of Nigeria as a study testbed. From the testbed, technical data were collected for both a dedicated Wifi hotspot and Globacom WiMax infrastructure. The Wifi Tiplink access point, WiMax Distributed Control System (DCS) and a wireless router were all configured for the initial pathloss experimentation. MATLAB Script was developed for evaluation purposes considering the testbed. The results of the comparison show that WiMax offered a lower pathloss value compared with Wifi-network WiMax (IEEE 802.16). This makes WiMax optimal for wireless access communication with advantages such as being flexible, having long range, and offering high data capability.

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Angle-of-arrival assisted Radio Interferometry (ARI) target localization

Cited by 22 publications

References 7 publications

Feasibility and limits of wi-fi imaging

Feasibility and limits of wi-fi imaging

A Survey on Localization for Mobile Wireless Sensor Networks

Analysis of Addax-Sinopec Outdoor Pathloss Behavior for WiFi and WiMAX Infrastructure

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