Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

Nguyen, Ngoc M; Tran, Le Chung; Safaei, Farzad; Phung, Son Lam; Vial, Peter James; Huynh, Nam N; Cox, Anne; Harada, Theresa; Barthélemy, Johan

doi:10.3390/s19112633

Cited by 10 publications

(9 citation statements)

References 67 publications

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“…Thus, this paper aimed to estimate the step length based on the received signal strength indicator (RSSI) method in both walking and jogging activities in indoor and outdoor scenarios. The RSSI has been widely employed in distance estimation, and it might provide reliable performance [12][13][14][15][16][17], especially for measurements in line-of-sight (LOS) paths over short distances, such as the step length measurements in this paper. The step length in this paper refers to the average distance between two ankles of the person under test when the person is walking or jogging at a normal and equal pace.…”

Section: Introductionmentioning

confidence: 99%

Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios

Yang

Tran

Safaei

2022

Sensors

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In this paper, human step length was estimated based on wireless channel properties and the received signal strength indicator (RSSI) method. Path loss between two ankles of the person under test was converted from the RSSI, which was measured using our developed wearable transceivers with embedded micro-controllers in four scenarios, namely indoor walking, outdoor walking, indoor jogging, and outdoor jogging. For brevity, we call it on-ankle path loss. The histogram of the on-ankle path loss showed clearly that there were two humps, where the second hump was closely related to the maximum path loss, which, in turn, corresponded to the step length. This histogram can be well approximated by a two-term Gaussian fitting curve model. Based on the histogram of the experimental data and the two-term Gaussian fitting curve, we propose a novel filtering technique to filter out the path loss outliers, which helps set up the upper and lower thresholds of the path loss values used for the step length estimation. In particular, the upper threshold was found to be on the right side of the second Gaussian hump, and its value was a function of the mean value and the standard deviation of the second Gaussian hump. Meanwhile, the lower threshold lied on the left side of the second hump and was determined at the point where the survival rate of the measured data fell to 0.68, i.e., the cumulative distribution function (CDF) approached 0.32. The experimental data showed that the proposed filtering technique resulted in high accuracy in step length estimation with errors of only 10.15 mm for the indoor walking, 4.40 mm for the indoor jogging, 4.81 mm for the outdoor walking, and 10.84 mm for the outdoor jogging scenarios, respectively.

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Section: Introductionmentioning

confidence: 99%

Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios

Yang

Tran

Safaei

2022

Sensors

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“…As a well-known localization positioning system for outdoor, GPS may fail to meet the accuracy requirements for some indoor environments, because the electromagnetic wave is severely attenuated by obstacles or is even forbidden in some situations, such as in military operations. Therefore, non-GPS localization has gained much interest from both researchers and industries [ 5 ]. Range-free and range-based are two categories of non-GPS localization.…”

Section: Introductionmentioning

confidence: 99%

“…By finding the strongest signal from the received power spectrum, the position of the unknown node can be identified. A weighted combination methods of RSSI and AOA was explored in Reference [ 5 ]. The observation indicates that the RSSI component is more sensitive to shadowing than the AOA component in vehicular ad hoc network (VANET) scenarios.…”

Section: Introductionmentioning

confidence: 99%

Step Length Measurements Using the Received Signal Strength Indicator

Yang

Tran

Safaei

2021

Sensors

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In this paper, portable transceivers with micro-controllers and radio frequency modules are developed to measure the received signal strength, path loss, and thus the distance between the human ankles for both indoor and outdoor environments. By comparing the experimental results and the theoretical model, a path loss model between transceivers attached to the subject’s ankles is derived. With the developed experimental path loss model, the step length can be measured relatively accurately, despite the imperfections of hardware devices, with the distance errors of a centimeter level. This paper, therefore, helps address the need for a distance measurement method that has fewer health concerns, is accurate, and is less affected by occlusions and confined spaces. Our findings possibly lay a foundation for some important applications, such as the measurement of gait speed and localization of the human body parts, in wireless body area networks.

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“…The two most common range-based non-GPS localization methods, i.e., RSSI and AOA, have been intensively studied at RF over the last decade. However, an in-depth analysis of methods to combine these two cues is still unavailable, although weighted sums have been proposed (Nguyen et al, 2019 ). We will study such combinations in our future work.…”

Section: Resultsmentioning

confidence: 99%

Bio-Inspired Radio-Frequency Source Localization Based on Cochlear Cross-Correlograms

Wang

Mandal

2021

Front. Neurosci.

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This paper describes a bio-inspired radio frequency (RF) scene analysis system based on cross-correlating the outputs of two single-chip RF spectrum analyzers. The latter are implemented using digitally-programmable “RF cochlea” chips (in 65 nm CMOS) that integrate a transmission-line active cochlear model, consisting of 50 parallel exponentially-spaced stages for analyzing the radio spectrum from 1.0 to 8.3 GHz, together with an output encoding network. The encoders convert the analog outputs of all cochlear stages into parallel delta-sigma (Δ-Σ) modulated digital signals for real-time demodulation and analysis by a digital back-end processor. These outputs can also be multiplied with each other to generate cochlear correlation matrices (known as cross-correlograms). Simulation results demonstrate the use of cross-correlograms for wide-range time-delay estimation and real-time multi-source localization at different frequencies and input signal-to-noise (SNR) ratios. Over-the-air measurement results from an experimental two-channel RF scene analysis prototype confirm the use of such time-delay estimates, which are analogous to interaural time differences (ITDs) in the auditory system, for azimuthal source localization at 3.4 GHz. In addition, differences in received signal strength at the two cochleas, which are analogous to interaural level differences (ILD) in biology, are also used to localize RF sources.

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Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

Cited by 10 publications

References 67 publications

Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios

Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios

Step Length Measurements Using the Received Signal Strength Indicator

Bio-Inspired Radio-Frequency Source Localization Based on Cochlear Cross-Correlograms

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