Measurements of the effects of multipath interference on timing accuracy in a cellular radio positioning system

Faragher, Ramsey; Duffett-Smith, Peter

doi:10.1049/iet-rsn.2009.0287

Cited by 8 publications

(8 citation statements)

References 5 publications

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“…System applications use signal strength fingerprinting [9], message content [10] or message flight time [11][12] to derive geolocation data from the RF signals of opportunity. These systems each have their own limitations; however the need for prior signal mapping information and poor performance in multipath environments [13] [14] are limitations in all systems [15].…”

Section: Current Geolocation Solutionsmentioning

confidence: 99%

“…ToA Estimation [13] 300 Quoted performance is only for 'mid-urban' environments. Dense urban likely to be worse.…”

Section: Technique Typical Error (3σ) (M) Notesmentioning

confidence: 99%

“…The performance of the proposed sinusoidal Kalman filter based system will be simulated in a typical urban environment. The aim of the simulation is to allow an analysis of the proposed approach alongside that of the most widely adopted prior art [13], enabling a comparison of performance to be made. The simulation has created a radio fingerprint of the dense urban environment shown in Figure 4 with signals generated from point A.…”

Section: Simulationmentioning

confidence: 99%

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Signals of opportunity geolocation methods for urban and indoor environments

2017

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Motivated by the geolocation requirements of future mobile network applications such as portable internet of things (IoT) devices and automated airborne drone systems, this paper aims to provide techniques for improving device geolocation estimates in urban and indoor locations. In these applications low size, weight and power are vital design constraints. This paper proposes methods for improving the geolocation estimate available to a system in indoor and urban environments without the need for addition sensing or transmitting hardware. This paper proposes novel system application techniques that enable the integration of signals of opportunity, providing a robust geolocation estimate without any additional hardware. The proposed method utilizes a sinusoidal Kalman filter architecture to analyse raw radio frequency (RF) signals that surround a system in urban and indoor environments. The introduced techniques efficiently analyse the raw RF data from any signal of opportunity and combine it with higher level geolocation sensors to provide an improved geolocation estimate. The improvements achieved by the system in a range of environments have been simulated, analysed and compared to the results obtained using the prior art. These improvements have been further validated and benchmarked by hardware test. The results obtained provide evidence that the efficient use of signals of opportunity coupled with common navigation sensors can provide a robust and reliable geolocation system in indoor and urban environments.

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Section: Current Geolocation Solutionsmentioning

confidence: 99%

“…ToA Estimation [13] 300 Quoted performance is only for 'mid-urban' environments. Dense urban likely to be worse.…”

Section: Technique Typical Error (3σ) (M) Notesmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

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Signals of opportunity geolocation methods for urban and indoor environments

2017

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“…As well as a significant improvement in the Poisson distribution, the UWB based edge detection algorithm removes the erroneous outliers seen at ≈ 0.7 m and ≈ 1.1 m error in the threshold detection algorithm. This behaviour may account for the high multipath uncertainty seen in (Faragher R. M., 2007) where a simple threshold detection algorithm was used to detect the ToA to estimate range.…”

Section: Technique Validationmentioning

confidence: 99%

Improving Signal of Opportunity Localisation Estimates in Multipath Environments

Mansfield

Ghita

Ambroze³

2015

Proceedings of the Fourth International Conference on Telecommunications and Remote Sensing

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Network based geographic localisation has been widely researched in recent years due to the need to locate mobile data communication nodes to a level of accuracy equivalent to that provided by global navigation satellite systems (GNSS) in multipath urban and indoor environments. This paper investigates whether direct sequence spread spectrum (DSSS) signal processing can be applied to narrow-band radio channels to improve the ranging estimates. The DSSS signal processing application is then developed further to provide a method of deriving a measurement confidence indicator, allowing the optimisation of time separated measurements in a dynamic signals of opportunity radio environment. A set of validation tests demonstrates that the proposed method provides a significant improvement in the accuracy and robustness of the ranging estimate compared to simple threshold analysis in multipath environments.

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“…These co-ordinate systems are combined by dynamic, uncertain transforms which allow significantly more flexibility in introducing new localisation systems. The architecture has been evaluated using a series of localisation systems including traditional inertial navigation systems, visual place recognition [3], cellular transmitter tracking [4], visually stabilised inertial [5], visual odometry [6] and Inertial Measurement Unit/SLAM hybrids [7]. A selection of these systems allows for cost-effective, indefinite-range autonomous navigation in GPS-intermittent and denied environments.…”

Section: Localisationmentioning

confidence: 99%

The Next Generation of Unmanned Ground Vehicles

Hester¹,

Smith²,

Day³

et al. 2012

Measurement and Control

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Over the last decade, the development of Unmanned Ground Vehicles (UGVs) has received significant attention through technology competitions, such as the DARPA Grand Challenges, where an unmanned vehicle autonomously navigated across a desert or through semiurban roads. Although this marked a significant step forward in autonomous navigation, the current generation of UGVs are only capable of operating in controlled environments where the dynamics of a scene are wellunderstood. For example in both of the DARPA Grand Challenges, the participants were given detailed maps and the environment was carefully controlled during the competition. The next generation of UGVs will need to operate in uncontrolled environments where the terrain and infrastructure is uncertain and humans could be present. This paper discusses the challenges and current developments in the areas of sensing, localisation and planning to realise the next generation of UGVs.

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Measurements of the effects of multipath interference on timing accuracy in a cellular radio positioning system

Cited by 8 publications

References 5 publications

Signals of opportunity geolocation methods for urban and indoor environments

Signals of opportunity geolocation methods for urban and indoor environments

Improving Signal of Opportunity Localisation Estimates in Multipath Environments

The Next Generation of Unmanned Ground Vehicles

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