Performance Analysis of a 60-GHz Radar for Indoor Positioning and Tracking

Antonucci, Alessandro; Corrà, Michele; Ferrari, A. J.; Fontanelli, Daniele; Fusari, E.; Macii, David; Palopoli, Luigi

doi:10.1109/ipin.2019.8911764

Cited by 20 publications

(19 citation statements)

References 24 publications

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“…In this section, we first briefly explain different data collection approaches and their fundamentals, including suitable antenna types and designs, and then describe the variables that are measured. Hardware calibration [65], [90], [94], [96], [141], [142] and physical noise reduction [109] are considered to be outside the scope of this paper and will therefore not be addressed.…”

Section: A Collection Systemsmentioning

confidence: 99%

“…The goal was to reduce computational overhead on resource constrained 2) Automatic Feature Mapping: Automatic feature mapping methods used in the millimeter wave sensing applications mainly aim at dimensionality reduction. Several tracking applications that utilize point cloud frames either use clustering [46], [93] or the Kalman filter's prediction process [55], [94], [96], [114] to reduce point clouds into point cloud cluster centroid values. Since the number of point clouds per frame is unknown, a clustering algorithm that does not require a number of clusters to be defined a priori is required [46].…”

Section: Feature Extractionmentioning

confidence: 99%

“…Several Bayesian filters exist, such as the custom Bayesian [45], [185], particle [44], [136], α − β [128], Kalman [46], [53], [58], extended Kalman [55], [94], [96], [114], [115], [135], [186], fusion extended Kalman [95], [146], unscented Kalman [89], fusion adaptive Kalman [51], and adaptive Sage-Husa Kalman [52], [61] filter. The Kalman filter [219], under linear, quadratic, and Gaussian assumptions, can represent the state transition and observation functions x t = g(x t−1 , pn t ) and s t = h(x t , mn t ) as a set of linear equations.…”

Section: Analytical Modelingmentioning

confidence: 99%

“…Association/allocation models either use combinatorial optimization [46], [185], a gating function [55], [94], [96], [114], template model matching [201] or landmark association [89], [132]. These models associate input data to an existing entity or create new entities based on an optimization criterium.…”

Section: Analytical Modelingmentioning

confidence: 99%

“…The authors in [47], [56], [145] compare several self-created models to each other. Authors in [46], [55], [72], [89], [94], [96], [114], [127], [132], [134], [135], [143], [185] incorporate different processes in their millimeter wave sensing application pipeline that use a distinct model. Several papers use pipelines that include a tree or sequential set of multiple models coming from both the data and model driven paradigms.…”

Section: White Box Grey Box Shallow Black Box Deep Black Boxmentioning

confidence: 99%

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Millimeter Wave Sensing: A Review of Application Pipelines and Building Blocks

et al. 2021

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The increasing bandwidth requirement of new wireless applications has lead to standardization of the millimeter wave spectrum for high-speed wireless communication. The millimeter wave spectrum is part of 5G and covers frequencies between 30 and 300 GHz that correspond to wavelengths ranging from 10 to 1 mm. Although millimeter wave is often considered as a communication medium, it has also proved to be an excellent 'sensor', thanks to its narrow beams, operation across a wide bandwidth, and interaction with atmospheric constituents. In this paper, which is to the best of our knowledge the first review that completely covers millimeter wave sensing application pipelines, we provide a comprehensive overview and analysis of different basic application pipeline building blocks, including hardware, algorithms, analytical models, and model evaluation techniques. The review also provides a taxonomy that highlights different millimeter wave sensing application domains. By performing a thorough analysis, complying with the systematic literature review methodology and reviewing 165 papers, we not only extend previous investigations focused only on communication aspects of the millimeter wave technology and using millimeter wave technology for active imaging, but also highlight scientific and technological challenges and trends, and provide a future perspective for applications of millimeter wave as a sensing technology.

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