A Robust Visual-Aided Inertial Navigation Algorithm for Pedestrians

Real-time and robust state estimation for pedestrians is a challenging problem under the satellite denial environment. The zero-velocity-aided foot-mounted inertial navigation system, with the shortcomings of unobservable heading, error accumulation, and poorly adaptable parameters, is a conventional method to estimate the pose relative to a known origin. Visual and inertial fusion is a popular technology for state estimation over the past decades, but it cannot make full use of the movement characteristics of pedestrians. In this paper, we propose a novel visual-aided inertial navigation algorithm for pedestrians, which improves the robustness in the dynamic environment and for multi-motion pedestrians. The algorithm proposed combines the zero-velocity-aided INS with visual odometry to obtain more accurate pose estimation in various environments. And then, the parameters of INS have adjusted adaptively via taking errors between fusion estimation and INS outputs as observers in the factor graphs. We evaluate the performance of our system with real-world experiments. Results are compared with other algorithms to show that the absolute trajectory accuracy in the algorithm proposed has been greatly improved, especially in the dynamic scene and multi-motions trials.

Three-frequency models for determining the orientation of a solid body taking into account the vibration environment

Two new three-frequency reference models of solid motion taking into account the vibrational environment are proposed. They are based on a four-frequency reference model of rotation [1], which implements rotations according to Krylov angles. For the developed models the analytical dependences for quasi-coordinates, projections of the angular velocity vector and components of the quaternion of orientation corresponding to such rotational motion are obtained. The urgency of taking into account the influence of vibration in traffic modeling on the basis of domestic and foreign literature in the field of navigation, including for the last 10 years. The main sources of vibration are described in detail and what types of oscillations they correspond to - harmonic oscillations occur in moving elements of onboard systems, such as the engine rotor, and in the engine unit and its units there are oscillations that have the character of random broadband noise. Methods of correction of such influence for increase of accuracy of definition of orientation of object are analyzed. The location of the components of the platformless inertial navigation system relative to the vibration sources is considered to be related to the strength of the influence of the vibration environment on the accuracy of the obtained data. Numerical implementations of the models are obtained and the drift error for the third-order orientation algorithm is estimated for several sets of specified parameters in a certain way. The parameters are chosen arbitrarily, but taking into account the existing restrictions on angular motion. The corresponding figures show the result for one of these sets of numerical values (which shows the result of the research in the most detail). The obtained results are compared with the corresponding results for the four-frequency rotation model [1]. The expediency of using new three-frequency models under certain conditions is shown.

Evaluation of permissible amplitudes of external impact on free-of-platform inertial navigation systems

In modern aerospace technology, strapdown inertial navigation systems (SINS) are widely used, using fiber-optic (FOG) or ring laser (CLG) gyroscopes. During the operation of such systems, the sensitivity axes are rotated relative to the basic coordinate system. The resulting angles between the axes of the base coordinate system and the axes of sensitivity of the navigation system (non-orthogonality) are one of the factors leading to an increase in the measurement errors of the device, which affects the measurement accuracy. During operation, the system is affected by vibrations of various nature, the impact of which can contribute to the appearance of non-orthogonality. The purpose of this work is to determine the maximum permissible vibration amplitudes affecting the SINS body according to the permissible values ​​of the deviation of the FOG sensitivity axes for two variants of the SINS layout. An approach to determining the permissible amplitudes of an external harmonic impact on the unit of a strapdown inertial navigation system based on fiber-optic or ring laser gyroscopes is considered. A design scheme, mathematical and finite element models for calculating natural frequencies and forced oscillations of a strapdown inertial navigation system unit have been developed. In various frequency ranges, numerical calculations have determined the boundary values ​​of the amplitudes of the external harmonic impact on the base of specific configurations of the SINS assembly. It has been established that dangerous states take place in the region of the 1st natural frequency of the system, as well as near higher frequencies. Comparison of the results for design options 1 and 2 allows us to conclude that in order to weaken the effect of vibrations on the accuracy of the SINS unit, it is advisable that the lowest natural vibration frequencies for the SINS assembly be as high as possible (more than 1000 Hz). Key words: vibration; fiber optic gyroscope; strapdown inertial navigation system; finite element method; natural frequencies and modes of vibration.

SUPPORT VECTOR MACHINE FOR DETERMINING EULER ANGLES IN AN INERTIAL NAVI-GATION SYSTEM

The paper discusses the improvement of the accuracy of an inertial navigation system created on the basis of MEMS sensors using machine learning (ML) methods. As input data for the classifier, we used information obtained from a developed laboratory setup with MEMS sensors on a sealed platform with the ability to adjust its tilt angles. To assess the effectiveness of the models, test curves were constructed with different values of the parameters of these models for each core in the case of a linear, polynomial radial basis function. The inverse regularization parameter was used as a parameter. The proposed algo-rithm based on MO has demonstrated its ability to correctly classify in the presence of noise typical for MEMS sensors, where good classification results were obtained when choosing the optimal values of hy-perparameters.

Spread Spectrum Sound with TDMA and INS Hybrid Navigation System for Indoor Environment

Indoor navigation plays an essential role in agricultural robots that operate in greenhouses. One of the most effective methods for indoor navigation is the spread spectrum sound (SS-sound) system. In this system, the time of arrival (ToA) of the spread spectrum modulated sound is used for localization. However, there is a near-far problem. Transmitting the SS-sound from multiple anchors using time division multiple access (TDMA) is adequate to solve the near-far problem. However, localization is impossible because the ToA from multiple anchors cannot be simultaneously acquired. To solve this problem, a method for combining the SS-sound system with TDMA and an inertial navigation system is proposed in this study. The effectiveness of the proposed method was demonstrated through numerical simulations of a ground robot and experimentally using a crawler robot.

Researching and building a method for testing and adjusting the strapdown inertial navigation system

The strap-down inertial navigation system (SINS) is widely used and becoming very important in many areas, especially in the arms industry when the GPS signal is lost or not reliable. To ensure the precision of the system, in addition to optimizing the algorithm for the strap-down inertial navigation system, the testing, and adjusting of the SINS system when installed on vehicles also play a vital role. In the article, a method of displaying SINS data on a digital map is proposed. Furthermore, the article also proposes a method to assess the influence of misalignment angles on the navigation accuracy and how to estimate and correct them.

An Indoor Navigation Algorithm Using Multi-Dimensional Euclidean Distance and an Adaptive Particle Filter

The inertial navigation system has high short-term positioning accuracy but features cumulative error. Although no cumulative error occurs in WiFi fingerprint localization, mismatching is common. A popular technique thus involves integrating an inertial navigation system with WiFi fingerprint matching. The particle filter uses dead reckoning as the state transfer equation and the difference between inertial navigation and WiFi fingerprint matching as the observation equation. Floor map information is introduced to detect whether particles cross the wall; if so, the weight is set to zero. For particles that do not cross the wall, considering the distance between current and historical particles, an adaptive particle filter is proposed. The adaptive factor increases the weight of highly trusted particles and reduces the weight of less trusted particles. This paper also proposes a multidimensional Euclidean distance algorithm to reduce WiFi fingerprint mismatching. Experimental results indicate that the proposed algorithm achieves high positioning accuracy.