Open Access

Ultra wide band (UWB) signals are well suited both for short-range wireless communication and for high-precision localization applications. Channel impulse response (CIR) analysis in UWB systems is a major element in localization estimation. In this paper, practical aspects of CIR are presented. I.e. a technique for the construction of the accumulated echo-gram of a multipath delayed signal is proposed. Decawave hardware was used to demonstrate the technique of analysis of fine structure of signals with a sub-nanosecond resolution. Temporal stability, reliability and two-way characteristics of such echo-grams are discussed as well. The results of using two EVK1000 radio modules as a radar installation to detect a target in indoor environments prove that a low cost UWB intrusion detection and through-the-wall-vision systems might be developed using the proposed technique.

The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach. A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm. The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained.

Ranging errors are inevitable in all local positioning systems, including those based on Time-of-Flight (ToF) technique. Results of experiments show that the major cause for these errors is a signal degradation from multipath propagation. This effect is especially critical in case of Non-Light-of-Sight (NLOS) conditions. This paper describes causes that affects ranging errors for nanoLOC™-TOF-technology and presents estimations for the probability density functions of such errors under different NLOS conditions. The provided estimations allow the improvement of the accuracy of the localization through the subsequent mitigation of the ranging errors from the measurements. Additionally, it is proposed to increase the number of cases of NLOS-conditions for the improvement of the accuracy.

The application of leaky feeder (radiating) cables is a common solution for the implementation of reliable radio communication in huge industrial buildings, tunnels and mining environment. This paper explores the possibilities of leaky feeders for 1D and 2D localization in wireless systems based on time of flight chirp spread spectrum technologies. The main focus of this paper is to present and analyse the results of time of flight and received signal strength measurements with leaky feeders in indoor and outdoor conditions. The authors carried out experiments to compare ranging accuracy and radio coverage area for a point-like monopole antenna and for a leaky feeder acting as a distributed antenna. In all experiments RealTrac equipment based on nanoLOC radio standard was used. The estimation of the most probable path of a chirp signal going through a leaky feeder was calculated using the ray tracing approach. The typical non-line-of-sight errors profiles are presented. The results show the possibility to use radiating cables in real time location technologies based on time-of-flight method.

During the day-to-day exploitation of localization systems in mines, the technical staff tends to incorrectly rearrange radio equipment: positions of devices may not be accurately marked on a map or their positions may not correspond to the truth. This situation may lead to positioning inaccuracies and errors in the operation of the localization system.This paper presents two Bayesian algorithms for the automatic corrections of positions of the equipment on the map using trajectories restored by the inertial measurement units mounted to mobile objects, like pedestrians and vehicles. As a basis, a predefined map of the mine represented as undirected weighted graph was used as input. The algorithms were implemented using the Simultaneous Localization and Mapping (SLAM) approach.The results prove that both methods are capable to detect misplacement of access points and to provide corresponding corrections. The discrete Bayesian filter outperforms the unscented Kalman filter, which, however, requires more computational power.