Fast Radio Map Construction by using Adaptive Path Loss Model Interpolation in Large-Scale Building.

The radio map construction is usually time-consuming and labor-sensitive in indoor fingerprinting localization. We propose a fast construction method by using an adaptive path loss model interpolation. Received signal strength (RSS) fingerprints are collected at sparse reference points by using multiple smartphones based on crowdsourcing. Then, the path loss model of an access point (AP) can be built with several reference points by the least squares method in a small area. Afterwards, the RSS value can be calculated based on the constructed model and corresponding AP's location. In the small area, all models of detectable APs can be built. The corresponding RSS values can be estimated at each interpolated point for forming the interpolated fingerprints considering RSS loss, RSS noise and RSS threshold. Through combining all interpolated and sparse reference fingerprints, the radio map of the whole area can be obtained. Experiments are conducted in corridors with a length of 211 m. To evaluate the performance of RSS estimation and positioning accuracy, inverse distance weighted and Kriging interpolation methods are introduced for comparing with the proposed method. Experimental results show that our proposed method can achieve the same positioning accuracy as complete manual radio map even with the interval of 9.6 m, reducing 85% efforts and time of construction.

A Tightly-Coupled GPS/INS/UWB Cooperative Positioning Sensors System Supported by V2I Communication.

This paper investigates a tightly-coupled Global Position System (GPS)/Ultra-Wideband (UWB)/Inertial Navigation System (INS) cooperative positioning scheme using a Robust Kalman Filter (RKF) supported by V2I communication. The scheme proposes a method that uses range measurements of UWB units transmitted among the terminals as augmentation inputs of the observations. The UWB range inputs are used to reform the GPS observation equations that consist of pseudo-range and Doppler measurements and the updated observation equation is processed in a tightly-coupled GPS/UWB/INS integrated positioning equation using an adaptive Robust Kalman Filter. The result of the trial conducted on the roof of the Nottingham Geospatial Institute (NGI) at the University of Nottingham shows that the integrated solution provides better accuracy and improves the availability of the system in GPS denied environments. RKF can eliminate the effects of gross errors. Additionally, the internal and external reliabilities of the system are enhanced when the UWB observables received from the moving terminals are involved in the positioning algorithm.

A Vondrak low pass filter for IMU sensor initial alignment on a disturbed base.

The initial alignment of the Inertial Measurement Unit (IMU) is an important process of INS to determine the coordinate transformation matrix which is used in the integration of Global Positioning Systems (GPS) with Inertial Navigation Systems (INS). In this paper a novel alignment method for a disturbed base, such as a vehicle disturbed by wind outdoors, implemented with the aid of a Vondrak low pass filter, is proposed. The basic principle of initial alignment including coarse alignment and fine alignment is introduced first. The spectral analysis is processed to compare the differences between the characteristic error of INS force observation on a stationary base and on disturbed bases. In order to reduce the high frequency noise in the force observation more accurately and more easily, a Vondrak low pass filter is constructed based on the spectral analysis result. The genetic algorithms method is introduced to choose the smoothing factor in the Vondrak filter and the corresponding objective condition is built. The architecture of the proposed alignment method with the Vondrak low pass filter is shown. Furthermore, simulated experiments and actual experiments were performed to validate the new algorithm. The results indicate that, compared with the conventional alignment method, the Vondrak filter could eliminate the high frequency noise in the force observation and the proposed alignment method could improve the attitude accuracy. At the same time, only one parameter needs to be set, which makes the proposed method easier to implement than other low-pass filter methods.