where xt+1 is the position and orientation of the robot (with respect to a reference frame) at time t + 1, with (ξ, η) giving the x and y coordinates and θ the angle (with respect to the x-axis) that the robot is facing. The robot has two drive wheels, of radius r on an axle of length d. During time period t the right wheel is believed to rotate at a velocity of φRt and the left at a velocity of φLt. In this example, these velocities are fixed with φRt = 0.4 and φLt = 0.1. The state update function, F , calculates where the robot should be at each time point, given its previous position. However, in reality, there is some random fluctuation in the velocity of the wheels, for example, due to slippage. Therefore the actual position of the robot and the position given by equation F will differ. The magnitude of these random fluctuations is included in the model through Σx.

Unscented Kalman Filterの計測への応用に関する研究

This chapter reviews our current knowledge of the gravity and topography of the terrestrial planets and describes the methods that are used to analyze these data. A general review of the mathematical formalism that is used in describing gravity and topography is first given. Next, the basic properties of Earth, Venus, Mars, Mercury, and the Moon are characterized. Following this, the relationship between gravity and topography is quantified, and techniques by which geophysical parameters can be constrained are detailed. Analysis methods include crustal thickness modeling, geoid/topography ratios, spectral admittance and correlation functions, and localized spectral analysis and wavelet techniques. Finally, the major results that have been obtained by modeling the gravity and topography of Earth, Venus, Mars, Mercury, and the Moon are summarized.

Gravity and Topography of the Terrestrial Planets

The availability of high-resolution global digital elevation data sets has raised a growing interest in the feasibility of obtaining their spherical harmonic representation at matching resolution, and from there in the modelling of induced gravity perturbations. We have therefore estimated spherical Bouguer and Airy isostatic anomalies whose spherical harmonic models are derived from the Earth’s topography harmonic expansion. These spherical anomalies differ from the classical planar ones and may be used in the context of new applications. We succeeded in meeting a number of challenges to build spherical harmonic models with no theoretical limitation on the resolution. A specific algorithm was developed to enable the computation of associated Legendre functions to any degree and order. It was successfully tested up to degree 32,400. All analyses and syntheses were performed, in 64 bits arithmetic and with semi-empirical control of the significant terms to prevent from calculus underflows and overflows, according to IEEE limitations, also in preserving the speed of a specific regular grid processing scheme. Finally, the continuation from the reference ellipsoid’s surface to the Earth’s surface was performed by high-order Taylor expansion with all grids of required partial derivatives being computed in parallel. The main application was the production of a 1′ × 1′ equiangular global Bouguer anomaly grid which was computed by spherical harmonic analysis of the Earth’s topography–bathymetry ETOPO1 data set up to degree and order 10,800, taking into account the precise boundaries and densities of major lakes and inner seas, with their own altitude, polar caps with bedrock information, and land areas below sea level. The harmonic coefficients for each entity were derived by analyzing the corresponding ETOPO1 part, and free surface data when required, at one arc minute resolution. The following approximations were made: the land, ocean and ice cap gravity spherical harmonic coefficients were computed up to the third degree of the altitude, and the harmonics of the other, smaller parts up to the second degree. Their sum constitutes what we call ETOPG1, the Earth’s TOPography derived Gravity model at 1′ resolution (half-wavelength). The EGM2008 gravity field model and ETOPG1 were then used to rigorously compute 1′ × 1′ point values of surface gravity anomalies and disturbances, respectively, worldwide, at the real Earth’s surface, i.e. at the lower limit of the atmosphere. The disturbance grid is the most interesting product of this study and can be used in various contexts. The surface gravity anomaly grid is an accurate product associated with EGM2008 and ETOPO1, but its gravity information contents are those of EGM2008. Our method was validated by comparison with a direct numerical integration approach applied to a test area in Morocco–South of Spain (Kuhn, private communication 2011) and the agreement was satisfactory. Finally isostatic corrections according to the Airy model, but in spherical geometry, with harmonic coefficients derived from the sets of the ETOPO1 different parts, were computed with a uniform depth of compensation of 30 km. The new world Bouguer and isostatic gravity maps and grids here produced will be made available through the Commission for the Geological Map of the World. Since gravity values are those of the EGM2008 model, geophysical interpretation from these products should not be done for spatial scales below 5 arc minutes (half-wavelength).

Spherical harmonic modelling to ultra-high degree of Bouguer and isostatic anomalies

Optimal estimation

Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages

Spherical harmonic series, commonly used to represent the Earth’s gravitational field, are now routinely expanded to ultra-high degree (> 2,000), where the computations of the associated Legendre functions exhibit extremely large ranges (thousands of orders) of magnitudes with varying latitude. We show that in the degree-and-order domain, (l,m), of these functions (with full ortho-normalization), their rather stable oscillatory behavior is distinctly separated from a region of very strong attenuation by a simple linear relationship: \(m = \ell \sin \theta\), where θ is the polar angle. Derivatives and integrals of associated Legendre functions have these same characteristics. This leads to an operational approach to the computation of spherical harmonic series, including derivatives and integrals of such series, that neglects the numerically insignificant functions on the basis of the above empirical relationship and obviates any concern about their broad range of magnitudes in the recursion formulas that are used to compute them. Tests with a simulated gravitational field show that the errors in so doing can be made less than the data noise at all latitudes and up to expansion degree of at least 10,800. Neglecting numerically insignificant terms in the spherical harmonic series also offers a computational savings of at least one third.

On the computation and approximation of ultra-high-degree spherical harmonic series

Global Positioning System (GPS) has been used as a primary source of navigation in land and airborne applications. However, challenging environments cause GPS signal blockage or degradation, and prevent reliable and seamless positioning and navigation using GPS only. Therefore, multi-sensor based navigation systems have been developed to overcome the limitations of GPS by adding some forms of augmentation. The next step towards assured robust navigation is to combine information from multiple ground-users, to further improve the chance of obtaining reliable navigation and positioning information. Collaborative (or cooperative) navigation can improve the individual navigation solution in terms of both accuracy and coverage, and may reduce the system's design cost, as equipping all users with high performance multi-sensor positioning systems is not cost effective. Generally, ‘Collaborative Navigation’ uses inter-nodal range measurements between platforms (users) to strengthen the navigation solution. In the collaborative navigation approach, the inter-nodal distance vectors from the known or more accurate positions to the unknown locations can be established. Therefore, the collaborative navigation technique has the advantage in that errors at the user's position can be compensated by other known (or more accurate) positions of other platforms, and may result in the improvement of the navigation solutions for the entire group of users. In this paper, three statistical network-based collaborative navigation algorithms, the Restricted Least-Squares Solution (RLESS), the Stochastic Constrained Least-Squares Solution (SCLESS) and the Best Linear Minimum Partial Bias Estimation (BLIMPBE) are proposed and compared to the Kalman filter. The proposed statistical collaborative navigation algorithms for network solution show better performance than the Kalman filter.

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Network-based Collaborative Navigation in GPS-Denied Environment

The precise geolocation of buried unexploded ordnance (UXO) is a significant component of the detection, characterization, and remediation process. Traditional geolocation methods associated with these procedures are inefficient in helping to distinguish buried UXO from relatively harmless geologic magnetic sources or anthropic clutter items such as exploded ordnance fragments and agricultural or industrial artefacts. The integrated INS/GPS geolocation system can satisfy both high spatial resolution and robust, uninterrupted positioning requirements for successful UXO detection and characterization. To maximize the benefits from this integration, non-linear filtering strategies (such as the unscented Kalman filter) have been developed and tested using laboratory data. In addition, adaptive filters and smoothers have been designed to address variable or inaccurate a priori knowledge of the process noise of the system during periods of GPS unavailability. In this paper, we study and compare the improvement in the geolocation accuracy when the neural network approach is applied to aid the adaptive versions of the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). The test results show that the neural network based filters can improve overall position accuracy and can homogenize the performance of the integrated system over a range of relatively quiet to dynamic environments. Navigation-grade and medium-grade IMUs were compared and, with standard smoothing applied to the new filters, geolocation accuracy of 5 cm (13 cm) was achieved with the navigation- (medium-) grade unit within 8-second intervals that lack external control, which is at or close to the area-mapping accuracy requirement for UXO detection.

Neural Network Aided Adaptive Filtering and Smoothing for an Integrated INS/GPS Unexploded Ordnance Geolocation System

Reliable and precise navigation technology is essential for robust detection and discrimination of unexploded ordnance (UXO) in a wide range of field conditions, including GPS-challenged environment. Based on the fact that the UXO detection involves frequent stops, this paper proposes an adaptive ZUPT (AZUPT) algorithm in a sliding time window to guarantee the correct identification of the zero velocity condition and improve the position accuracy of UXO geolocation. Furthermore, a known zero velocity-based prefiltering method is used to remove INS sensor errors. A pushcart-based prototype in which the tactical-grade inertial measurement unit and geodetic-grade GPS receiver are mounted is designed for the geolocation system. Field test was undertaken, and simulated GPS outages were introduced to the data. The result shows that AZUPT precisely identified the zero velocity and greatly improved the positioning accuracy of the cart-mounted UXO geolocation system.

Cart-Mounted Geolocation System for Unexploded Ordnance With Adaptive ZUPT Assistance

Accurate upward continuation of gravity anomalies supports future precision, free-inertial navigation systems, since the latter cannot by themselves sense the gravitational field and thus require appropriate gravity compensation. This compensation is in the form of horizontal gravity components. An analysis of the model errors in upward continuation using derivatives of the standard Pizzetti integral solution (spherical approximation) shows that discretization of the data and truncation of the integral are the major sources of error in the predicted horizontal components of the gravity disturbance. The irregular shape of the data boundary, even the relatively rough topography of a simulated mountainous region, has only secondary effect, except when the data resolution is very high (small discretization error). Other errors due to spherical approximation are even less important. The analysis excluded all measurement errors in the gravity anomaly data in order to quantify just the model errors. Based on a consistent gravity field/topographic surface simulation, upward continuation errors in the derivatives of the Pizzetti integral to mean altitudes of about 3,000 and 1,500 m above the mean surface ranged from less than 1 mGal (standard deviation) to less than 2 mGal (standard deviation), respectively, in the case of 2 arcmin data resolution. Least-squares collocation performs better than this, but may require significantly greater computational resources.

Jong-Ki Lee

Papers

On the computation and approximation of ultra-high-degree spherical harmonic series

Network-based Collaborative Navigation in GPS-Denied Environment

Neural Network Aided Adaptive Filtering and Smoothing for an Integrated INS/GPS Unexploded Ordnance Geolocation System

Cart-Mounted Geolocation System for Unexploded Ordnance With Adaptive ZUPT Assistance

Modeling errors in upward continuation for INS gravity compensation