Chris Rizos

Improving Adaptive Kalman Estimation in GPS/INS Integration

The central task of GPS/INS integration is to effectively blend GPS and INS data together to generate an optimal solution. The present data fusion algorithms, which are mostly based on Kalman filtering (KF), have several limitations. One of those limitations is the stringent requirement on precise a priori knowledge of the system models and noise properties. Uncertainty in the covariance parameters of the process noise (Q) and the observation errors (R) may significantly degrade the filtering performance. The conventional way of determining Q and R relies on intensive analysis of empirical data. However, the noise levels may change in different applications. Over the past few decades adaptive KF algorithms have been intensively investigated with a view to reducing the influence of the Q and R definition errors. The covariance matching method has been shown to be one of the most promising techniques. This paper first investigates the utilization of an online stochastic modelling algorithm with regards to its parameter estimation stability, convergence, optimal window size, and the interaction between Q and R estimations. Then a new adaptive process noise scaling algorithm is proposed. Without artificial or empirical parameters being used, the proposed adaptive mechanism has demonstrated the capability of autonomously tuning the process noise covariance to the optimal magnitude, and hence improving the overall filtering performance.

A critical evaluation of location based services and their potential

This Editorial lead article for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices will emerge means that much research is needed to inform these developments. The article reviews firstly: the science and technology of positioning, geographic information science, mobile cartography, spatial cognition and interfaces, information science, ubiquitous computing; and secondly the business, content and legal, social and ethics aspects, before synthesising the key issues for this new field.

Mine subsidence monitoring using multi-source satellite SAR images

Ground subsidence due to underground mining has posed a constant threat to the safety of surface infrastructure such as motorways, railways, power lines, and telecommunications cables. Traditional monitoring techniques like using levels, total stations and GPS can only measure on a point-by-point basis and hence are costly and time-consuming. Differential interferometric synthetic aperture radar (DINSAR) together with GPS and GIS have been studied as a complementary alternative by exploiting multi-source satellite SAR images over a mining site southwest of Sydney. Digital elevation models (DEMs) derived from ERS-1 and ERS-2 tandem images, photogrammetry, airborne laser scanning, and the Shuttle Radar Topography Mission were assessed based on ground survey data using levelling as well as GPS-RTK. The identified high quality DEM was then used in the DINSAR analysis. Repeat-pass acquisitions by the ERS-1, ERS-2, JERS-1, RADARSAT-1 and ENVISAT satellites were used to monitor mine subsidence in the region with seven active mine collieries. Sub-centimeter accuracy has been demonstrated by comparing DINSAR results against ground survey profiles. The ERS tandem DINSAR results revealed mm-level resolution.

How feasible is the use of magnetic field alone for indoor positioning

The use of magnetic field variations for positioning and navigation has been suggested by several researchers. In most of the applications, the magnetic field is used to determine the azimuth or heading. However, for indoor applications, accurate heading determination is difficult due to the presence of magnetic field anomalies. Here location fingerprinting methodology can take advantage of these anomalies. In fact, the more significant the local anomalies, the more unique the magnetic “fingerprint”. In general, the more elements in each fingerprint, the better for positioning. Unfortunately, magnetic field intensity data only consists of three components. Since true north (or magnetic north) is generally unknown, even with help of the accelerometer to detect the direction of the gravity, only two components can be extracted, i.e. the horizontal intensity and the vertical intensity (or total intensity and inclination). Furthermore, moving objects containing ferromagnetic materials and electronic devices may affect the magnetic field. Tests were carried out to investigate the feasibility of using magnetic field alone for indoor positioning. Possible solutions are discussed.

Applications of location-based services: a selected review

This article reviews a selected set of location–based services (LBS) that have been published in the research literature, focussing on mobile guides, transport support, gaming, assistive technology and health. The research needs and opportunities in each area are evaluated and the connections between each category of LBS are discussed. The review illustrates the enormous diversity of forms in which LBS are appearing and the wide range of application sectors that are represented. However, very few of these applications are implemented pervasively on a commercial basis as this is still challenging technically and economically.

Differences in RSSI readings made by different Wi-Fi chipsets: A limitation of WLAN localization

Wi-Fi positioning has found favour in environments which are traditionally challenging for GPS. The currently used method of Wi-Fi fingerprinting assumes that the devices used for training and locating perform identically. We have undertaken an experiment to determine how different devices behave in an empirical controlled test to identify the challenges and limitations which Wi-Fi fingerprinting positioning systems will face when deployed across many devices. We found that they performed significantly differently in respect to the mean reported signal strength — even those which came from the same vendor. We also found that multiple samples of the same device do not perform identically. Furthermore, it was found that certain devices were entirely unsuitable for positioning as they reported signal strength values uncorrelated with distance from the transmitter. Some other devices behaved in a way that made them poor candidates for use in fingerprinting. Temporal patterns were found in some wireless cards which suggest that filtering should be used. The tests also found that the use of 5GHz band signals had the potential to improve the accuracy of Wi-Fi location due to its higher stability compared to 2.4GHz. Ultimately however, the accuracy of Wi-Fi fingerprinting is limited due to many factors in the hardware and software design of Wi-Fi devices which affect the reported signal strength.

Multipath Mitigation of Continuous GPS Measurements Using an Adaptive Filter

Though state-of-the-art dual-frequency receivers are employed in the continuous Global Positioning System (CGPS) arrays, the CGPS coordinate time series are typically very noisy due to the effects of atmospheric biases, multipath, receiver noise, and so on, with multipath generally being considered the major noise contributor. An adaptive finite-duration impulse response filter, based on a least-mean-square algorithm, has been developed to derive a relatively noise-free time series from the CGPS results. Furthermore, this algorithm is suitable for real-time applications.Numerical simulation studies indicate that the adaptive filters is a powerful signal decomposer, which can significantly mitigate multipath effects. By applying the filter to both pseudorange and carrier phase multipath sequences derived from some experimental GPS data, multipath models have been reliably derived. It is found that the best multipath mitigation strategy is forward filtering using data on two adjacent days, which reduces the standard deviations of the pseudorange multipath time series to about one fourth its magnitude before correction and to about half in the case of carrier phase. The filter has been successfully applied to the pseudorange multipath sequences derived from CGPS data. The benefit of this techniques is that the affected observable sequences can be corrected, and then these corrected observables can be used to improve the quality of the GPS coordinate results.

MULTIPATH MITIGATION BY WAVELET ANALYSIS FOR GPS BASE STATION APPLICATIONS

Abstract It is well known that multipath disturbance is one of the major error sources impacting on high precision GPS positioning. The multipath disturbance is largely dependent on the receivers environment since satellite signals can arrive at the receiver via multiple paths, due to reflections from nearby objects such as trees, buildings, vehicles, etc. Although the multipath effect can be reduced by choosing sites without multipath reflectors or by using choke-ring antennas to mitigate the reflected signal, it is difficult to eliminate all multipath effects from GPS observations. Since the geometry between the GPS satellites and a specific receiver-reflector location repeats every sidereal day, multipath tends to exhibit the same pattern between consecutive days. This repetition can then be useful for verifying the presence of multipath through the analysis of observations made at a static receiver on different days. In this study, the authors apply a wavelet decomposition technique to extract multipath from GPS observations. The extracted multipath signature is then applied directly to the GPS observations to correct for the multipath effects. The results show that the proposed method can be used to significantly mitigate the multipath effects at a permanent GPS station.

Improving the computational efficiency of the ambiguity function algorithm

Techniques are described in this paper for improving the Ambiguity Function Method (AFM) for differential GPS positioning using phase observations, (a) that take advantage of optimal dual-frequency observable combinations to improve thereliability of the AFM, and (b) that significantly shorten the computation time necessary for the AFM. The procedure can be used for kinematic positioning applications if a Kalman filter predicted position is accurate enough as an initial position for the suggested AFM searching procedure, or pseudokinematic mode using say a triple-difference solution as an initial position for static positioning if the baseline length is short (typically <5km).

Reference station network based RTK systems-concepts and progress

The limitation of single base “real-time kinematic” (RTK) techniques is the distance between base receiver and the rover receiver due to distance-dependent biases, namely orbit bias, ionosphere bias and troposphere bias. Techniques have been developed to overcome this distance dependence using a network of GPS reference stations spread over a wide geographic area. Because the measurement biases will be modelled and corrected for, the positioning accuracy will be almost independent of the inter-receiver distance. Since the mid-1990s investigators have been investigating the optimal means of processing reference receiver data, and then providing ‘correction’ information to users, in real-time. This technique is now generally referred to as Network-RTK. In 1993 the International Association of Geodesy (IAG) established a Special Study Group on “Wide Area Modelling for Precise Satellite Positioning” . This paper focusses on the progress made during the last few years in designing Network-RTK architectures and the associated data processing algorithms and issues. Although many university investigators have been researching the fundamental challenges in functional and stochastic modelling, currently there is only one commercially available Network-RTK product, the Trimble VRS. However, with the use of the Internet as the primary data communication link, it is predicted that many more implementations of Network-RTK will come ‘online’, at various sites around the world, over the next few years.