相关论文: TuRF: Fast Data Collection for Fingerprint-based I…
Most existing fingerprints-based indoor localization approaches are based on some single fingerprints, such as received signal strength (RSS), channel impulse response (CIR), and signal subspace. However, the localization accuracy obtained…
Widespread adoption of indoor positioning systems based on WiFi fingerprinting is at present hindered by the large efforts required for measurements collection during the offline phase. Two approaches were recently proposed to address such…
Fingerprint-based indoor localization methods are promising due to the high availability of deployed access points and compatibility with commercial-off-the-shelf user devices. However, to train regression models for localization, an…
There has been an increasing tendency to move from outdoor to indoor lifestyle in modern cities. The emergence of big shopping malls, indoor sports complexes, factories, and warehouses is accelerating this tendency. In such an environment,…
An increasingly important requirement for many novel applications is sensing the positions of people, equipment, etc. GPS technology has proven itself as a successfull technology for positioning in outdoor environments but indoor no…
Location fingerprinting locates devices based on pattern matching signal observations to a pre-defined signal map. This paper introduces a technique to enable fast signal map creation given a dedicated surveyor with a smartphone and…
Accurate and personalized environment recognition is essential for seamless indoor positioning and optimized connectivity, yet traditional fingerprinting requires costly site surveys and lacks user-level adaptation. We present a…
Magnetic resonance Fingerprinting (MRF) is a relatively new multi-parametric quantitative imaging method that involves a two-step process: (i) reconstructing a series of time frames from highly-undersampled non-Cartesian spiral k-space data…
Building footprint maps are vital to many remote sensing applications, such as 3D building modeling, urban planning, and disaster management. Due to the complexity of buildings, the accurate and reliable generation of the building footprint…
Using WiFi signals for indoor localization is the main localization modality of the existing personal indoor localization systems operating on mobile devices. WiFi fingerprinting is also used for mobile robots, as WiFi signals are usually…
Although WiFi fingerprint-based indoor localization is attractive, its accuracy remains a primary challenge especially in mobile environments. Existing approaches either appeal to physical layer information or rely on extra wireless signals…
This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mobile carrier. Consequently, software installation on the…
One major bottleneck in the practical implementation of received signal strength (RSS) based indoor localization systems is the extensive deployment efforts required to construct the radio maps through fingerprinting. In this paper, we aim…
For the traditional fingerprinting-based positioning approach, it is essential to collect measurements at known locations as reference fingerprints during a training phase, which can be time-consuming and labor-intensive. This paper…
Artificial Intelligence (AI)-based radio fingerprinting (FP) outperforms classic localization methods in propagation environments with strong multipath effects. However, the model and data orchestration of FP are time-consuming and costly,…
This study describes a UWB and Machine Learning (ML)-based indoor positioning system. We propose a simple mathematical strategy to create data to reduce the job of measurements for fingerprint-based indoor localization systems. A…
Fingerprint-based passive localization enables high localization accuracy using low-cost UWB IoT radio sensors. However, fingerprinting demands extensive effort for data acquisition. The concept of channel charting reduces this effort by…
Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. Standard MRF reconstructs…
Finding trajectories and discovering motifs that are similar in large datasets is a central problem for a wide range of applications. Solutions addressing this problem usually rely on spatial indexing and on the computation of a similarity…
While a vast number of location-based services appeared lately, indoor positioning solutions are developed to provide reliable position information in environments where traditionally used satellite-based positioning systems cannot provide…