Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications, and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book’s practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include MATLAB computations, and the numerous end-of-chapter exercises include computational assignments. MATLAB/GNU Octave source code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.

贝叶斯滤波与平滑 (Bayesian filtering and smoothing)

Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target’s location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m), which performs 35.82% better than <3.99 m from the Propagation Model (PM) + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of <3.88 m at 90% of the time, which performs 49.58% more accurate than <8.00 m from the PM + EKF algorithm and 21.41% better than <4.94 m from the FP + EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.

Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons.

Indoor positioning systems (IPS) use sensors and communication technologies to locate objects in indoor environments. IPS are attracting scientific and enterprise interest because there is a big market opportunity for applying these technologies. There are many previous surveys on indoor positioning systems; however, most of them lack a solid classification scheme that would structurally map a wide field such as IPS, or omit several key technologies or have a limited perspective; finally, surveys rapidly become obsolete in an area as dynamic as IPS. The goal of this paper is to provide a technological perspective of indoor positioning systems, comprising a wide range of technologies and approaches. Further, we classify the existing approaches in a structure in order to guide the review and discussion of the different approaches. Finally, we present a comparison of indoor positioning approaches and present the evolution and trends that we foresee.

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Evolution of Indoor Positioning Technologies: A Survey

Fundamentals Of Neural Networks Architectures Algorithms And Applications

An accurate and reliable Indoor Positioning System (IPS) applicable to most indoor scenarios has been sought for many years. The number of technologies, techniques, and approaches in general used in IPS proposals is remarkable. Such diversity, coupled with the lack of strict and verifiable evaluations, leads to difficulties for appreciating the true value of most proposals. This paper provides a meta-review that performed a comprehensive compilation of 62 survey papers in the area of indoor positioning. The paper provides the reader with an introduction to IPS and the different technologies, techniques, and some methods commonly employed. The introduction is supported by consensus found in the selected surveys and referenced using them. Thus, the meta-review allows the reader to inspect the IPS current state at a glance and serve as a guide for the reader to easily find further details on each technology used in IPS. The analyses of the meta-review contributed with insights on the abundance and academic significance of published IPS proposals using the criterion of the number of citations. Moreover, 75 works are identified as relevant works in the research topic from a selection of about 4000 works cited in the analyzed surveys.

https://www.mdpi.com/1424-8220/19/20/4507/pdf

A Meta-Review of Indoor Positioning Systems.

Towards high accuracy GNSS real-time positioning with smartphones

Positioning in indoor environment is one of the most important and interesting topic in navigation system that still present numerous open problems to investigate. Many researchers are attempting to investigate on technologies able to reach valid location in an indoor space, where the well-known GNSS positioning systems are not able to operate. Among the many solutions proposed for location-based services, several wireless communications technologies have the potential to be employed for indoor positioning. In this paper, an Ultrawideband (UWB) indoor positioning commercial system is presented which exploits two-way time of flight (TWTF) to compute range measurements. These measurements are used in multi-lateration method to compute the position of a trans-receiver (TAG). Firstly, the calibration results have been shown, comparing the internal IMU sensor of UWB system with a mass-market one, using the angles measured thanks to the total station as reference. Secondly, we also have statically analysed the positioning and the ranging capabilities of the system in a favourable environment, as an indoor office room. The average 3D accuracy obtained from the test is 100 ± 25mm. Also the ranging measurements has been analysed as the raw data from which the Pozyx® inner algorithm starts to compute the positions. It has been demonstrated that the range accuracy is about 320 ± 30mm. After these first tests, the system has also been tested in a harsh environment in a narrow corridor where a horizontal accuracy of about 87.4 mm is obtained with a maximum ranging error of ±225 mm. The system and algorithms tested in this report gave almost similar performances in both environments.

Indoor positioning using Ultra-wide band (UWB) technologies: Positioning accuracies and sensors' performances

We present a methodology to use a UAV (unmanned aerial vehicle) to perform photogrammetric surveys and detailed geological mapping in mountain areas. This work is specially related to the presented case study with the aim to realize geomorphological maps from UAVs, since they can house different types of sensors and acquire data more rapidly and cheaply than traditional geological surveys directly obtained with field observations. This work explains how UAVs can obtain digital terrain models, orthophotos and 3D models in order to create slope and aspect maps for geological purposes. By integrating data from UAVs with geological surveys made on the field, geological maps can be produced where many of the geological elements are presented. This paper presents the integration of geomatics and geological techniques.Starting from UAV slope map and orthophotos, a new geological map was created in a faster and more detailed way compared to traditional geological survey on the ground. The application of t...

https://www.tandfonline.com/doi/pdf/10.1080/19475705.2016.1225228

Detailed geological mapping in mountain areas using an unmanned aerial vehicle: application to the Rodoretto Valley, NW Italian Alps

Landslides are one of the major geo-hazards which have constantly affected Italy especially over the last few years. In fact 82% of the Italian territory is affected by this phenomenon which destroys the environment and often causes deaths: therefore it is necessary to monitor these effects in order to detect and prevent these risks. Nowadays, most of this type of monitoring is carried out by using traditional topographic instruments (e.g. total stations) or satellite techniques such as global navigation satellite system (GNSS) receivers. The level of accuracy obtainable with these instruments is sub-centimetrical in post-processing and centimetrical in real-time; however, the costs are very high (many thousands of euros). The rapid diffusion of GNSS networks has led to an increase of using mass-market receivers for real-time positioning. In this paper, the performances of GNSS mass-market receiver are reported with the aim of verifying if this type of sensor can be used for real-time landslide monitoring...

Real-time monitoring for fast deformations using GNSS low-cost receivers

Forests are significant resources from an ecological, economic and social point of view. Their protection and management could greatly benefit from a complete knowledge of the shape and distribution of trees in forest stands. To this purpose, aerial surveys, especially through Airborne Laser Scanning (ALS), were carried out in the last years to acquire point clouds to be used in 3D models aimed at achieving an accurate description of tree crowns and terrain. However, airborne data acquisition is expensive and may provide poor results in case of dense foliage. Further, point cloud resolution is not very high, as models with a grid of 2-3 m are usually obtained. In order to implement more accurate 3D forest models, a feasible solution is the integration of point clouds obtained by aerial acquisition (ALS or photogrammetry) for the treetops and the terrain description, with information from terrestrial surveys. In this paper, we investigated the possible integration of point clouds obtained by Terrestrial Laser Scanner (TLS) with those collected by photogrammetric 3D models based on images captured by Unmanned Aerial Vehicle (UAV) in a test site located in northern Italy, with the aim of creating an accurate dataset of the forest site with high resolution and precision. The limits of ALS and TLS were bridged by aerial photogrammetry at low altitude (and vice versa). A 3D model of the study area was obtained with a resolution of 5 cm and a precision of 3 cm. Such model may be used in a wide range of applications in forestry studies, e.g., the reconstruction of 3D shapes of trees or the analysis of tree growth throught time. The implications of the use of such integrate approach as a support tool for decision-making in forest management are discussed.

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Paolo Dabove

Papers

Towards high accuracy GNSS real-time positioning with smartphones

Indoor positioning using Ultra-wide band (UWB) technologies: Positioning accuracies and sensors' performances

Detailed geological mapping in mountain areas using an unmanned aerial vehicle: application to the Rodoretto Valley, NW Italian Alps

Real-time monitoring for fast deformations using GNSS low-cost receivers

Integration between TLS and UAV photogrammetry techniques for forestry applications