An Improved Bluetooth Indoor Positioning Method Using Dynamic Fingerprint Window

Abstract

The weighted K-nearest neighbor algorithm (WKNN) is easily implemented, and it has been widely applied. In the large-scale positioning regions, using all fingerprint data in matching calculations would lead to high computation expenses, which is not conducive to real-time positioning. Due to signal instability, irrelevant fingerprints reduce the positioning accuracy when performing the matching calculation process. Therefore, selecting the appropriate fingerprint data from the database more quickly and accurately is an urgent problem for improving WKNN. This paper proposes an improved Bluetooth indoor positioning method using a dynamic fingerprint window (DFW-WKNN). The dynamic fingerprint window is a space range for local fingerprint data searching instead of universal searching, and it can be dynamically adjusted according to the indoor pedestrian movement and always covers the maximum possible range of the next positioning. This method was tested and evaluated in two typical scenarios, comparing two existing algorithms, the traditional WKNN and the improved WKNN based on local clustering (LC-WKNN). The experimental results show that the proposed DFW-WKNN algorithm enormously improved both the positioning accuracy and positioning efficiency, significantly, when the fingerprint data increased.

Indoor Positioning System Based on Bluetooth Low Energy Technology and a Nature-Inspired Optimization Algorithm

“…Since many new smartphones already have built-in Bluetooth capabilities, several authors are experimenting with those devices [31], which reduces the need for additional hardware. Inertial Measurement Units (IMUs), such as accelerometers and gyroscopes, are usually also present, and are combined successfully with the Bluetooth capabilities [32].…”

A study on the cabin indoor localization algorithm based on adaptive K-values

“…In recent years, with the rapid emergence of various large and complex buildings, there is an increasing demand for indoor positioning. For this reason, scholars at home and abroad have done a lot of research in the field of indoor positioning, and have also proposed a series of positioning techniques, 11,12 such as Wi-Fi, UWB, BLE, and ultrasonic. Each localization technology has its own advantages and drawbacks, and this section focuses on BLE-based indoor localization technology.…”

A Succinct Method for Non-Line-of-Sight Mitigation for Ultra-Wideband Indoor Positioning System

“…Although these systems can be applied to some unstructured and uncertain environments depending on their mapping ability, a serious drawback is that ultrasound and light cannot penetrate the obstacles, which limits those techniques to apply to IPSs [ 3 ]. The second category uses the radio signal to locate the target, such as WiFi [ 4 , 5 ], Bluetooth [ 6 , 7 ] and Ultra-wideband (UWB). Many previous research works explained the advantages and disadvantages of these methods in detail.…”

“…Applying WiFi to IPSs has the following benefits: wide distribution, low hardware cost, and high flexibility, but there are still some challenges like multipath, low accuracy and device heterogeneity [ 4 ]. The main advantages of Bluetooth technology are low hardware cost, low energy consumption, small size and high security [ 6 , 7 , 8 ]. On the other side, it still has some unavoidable drawbacks, like the calculation of the fingerprint algorithm increases dramatically when placed in a large indoor area.…”

“…On the other side, it still has some unavoidable drawbacks, like the calculation of the fingerprint algorithm increases dramatically when placed in a large indoor area. Furthermore, it is hard to improve the position accuracy to a centimetre lever [ 7 ]. UWB technology is up-and-coming for IPSs compared with those technologies.…”