Songlai Han

A Novel Method to Integrate IMU and Magnetometers in Attitude and Heading Reference Systems

Modern attitude and heading reference systems (AHRS) generally use Kalman filters to integrate gyros with some other augmenting sensors, such as accelerometers and magnetometers, to provide a long term stable orientation solution. The construction of the Kalman filter for the AHRS is flexible, while the general options are the methods based on quaternion, Euler angles, or Euler angle errors. But the quaternion and Euler angle based methods need to model system angular motions, and, meanwhile, all these three methods suffer from nonlinear problems which will increase the system complexities and the computational difficulties. This paper proposes a novel implementation method for the AHRS integrating IMU and magnetometer sensors. In the proposed method, the Kalman filtering is implemented to use the Euler angle errors to express the local level frame ( l frame) errors, rather than express the body frame ( b frame) errors as the customary methods do. A linear system error model based on the Euler angles errors expressing the l frame errors for the AHRS has been developed and the corresponding system observation model has been derived. This proposed method for AHRS does not need to model system angular motions and also avoids the nonlinear problem which is inherent in the commonly used methods. The experimental results show that the proposed method is a promising alternative for the AHRS.

Quantization and Colored Noises Error Modeling for Inertial Sensors for GPS/INS Integration

In this paper, modeling approaches for quantization and colored noises have been proposed. To accommodate the quantization noise, a modified inertial navigation system (INS) error dynamics is developed in this paper, and the quantization noise is incorporated into the modified INS error dynamics as augmenting driving noise. The three kinds of colored noises are modeled by using an equivalent differential equation driven by a unit white noise, and a technique is developed in this paper to augment the Kalman Filter of GPS/INS integration using this equivalent differential equation. Experimental test results show that the proposed stochastic error modeling approaches for quantization and colored noises significantly improves the accuracies of the estimated inertial drifts and the navigation solutions.

AN INSTANTANEOUS AMBIGUITY RESOLUTION PROCEDURE SUITABLE FOR MEDIUM-SCALE GPS REFERENCE STATION NETWORKS

Abstract There is a trend for the establishment of regional-scale GPS permanent receiver networks, for a variety of applications including to support high accuracy, carrier phase-based positioning for surveying and precise navigation. When implemented in real-time, GPS users located within the region enclosed by multiple GPS reference stations can precisely position by using, for example, the ‘correction terms’ generated and transmitted by the reference station network. For such a configuration one of the major challenges is that the integer ambiguities have to be resolved during the real-time processing of the reference network data in order to ensure the generation of the carrier phase corrections, even when the reference receivers are many tens of kilometres apart. Due to the presence of distance dependent errors in the double-differenced data (principally the ionospheric and tropospheric delays) reliable instantaneous (single epoch) ambiguity resolution is difficult in the case of medium-scale reference networks (defined here as where the reference stations are typically in the range 50–100km apart). In practice, the ambiguities among the reference stations can be correctly resolved during an initialization procedure, but the main challenge is to continuously resolve the new ambiguities that result when the tracked satellite experiences cycle slips, or after any long data gap, or when a new satellite rises. In this paper a three-step methodology is proposed which can be implemented in realtime. Firstly, the high correlation of the atmospheric delay between adjacent epochs is used to assist cycle-slip recovery and ambiguity resolution. Then these atmospheric biases are predicted for double-differenced observations on an epoch-by-epoch and satellite-by-satellite basis. Finally these predicted atmospheric biases are applied to an algorithm that can fix the new ambiguities after a long data gap or when a new satellite rises. Data from a set of reference stations spaced 80 km apart were used to test the effectiveness of the algorithm. The results indicate that the proposed methodology can provide reliable integer ambiguities for reference stations spaced many tens of kilometres apart.

A Novel Initial Alignment Scheme for Low-Cost INS Aided by GPS for Land Vehicle Applications

This paper proposes a novel mechanism for the initial alignment of low-cost INS aided by GPS. For low-cost INS, the initial alignment is still a challenging issue because of the high noises from low-cost inertial sensors. In this paper, a two-stage Kalman Filtering mechanism is proposed for the initial alignment of low-cost INS. The first stage is designed for the coarse alignment. To solve the problems encountered by the general coarse alignment approach, an INS error dynamic accounting for unknown initial heading error is developed, and the corresponding observation equation, taking into account the unknown heading error, is also developed. The second stage is designed for the fine alignment, where the classical INS error dynamics based on small attitude error is used. Experimental results indicate that the proposed alignment approach can complete the initial alignment more quickly and more accurately compared with the conventional approach.

Land Vehicle Navigation with the Integration of GPS and Reduced INS: Performance Improvement with Velocity Aiding

The movement of a land vehicle is constrained because the vehicle always remains on the Earths surface and only experiences small pitch and roll angles. So the GPS/INS integrated system for land vehicle navigation could be reconfigured to be the integration of GPS and reduced INS to cut down the costs. In a reduced INS, the vertical accelerometer and two horizontal gyros could be omitted from the system. But both theoretical analysis and experimental results show that this configuration may result in the divergence of height solution and large velocity errors. To improve the system performances, precise velocity derived from GPS carrier phase measurements, together with the GPS single point positioning solution, is used to aid the reduced INS. Field test results have demonstrated that first, the aiding from GPS precise velocity overcomes the divergence problem of the integrated height solutions and improves the integrated velocity and secondly the proposed novel integration scheme could achieve comparable navigation accuracy with that from the GPS and full INS integrated system.

Compensation for Stochastic Error of Gyros in a Dual-axis Rotational Inertial Navigation System

Zhichao Zheng, Songlai Han, Jin Yue and Linglong Yuan (Wuhan National Laboratory for Optoelectronics, School of Optoelectronic Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China) (College of Optoelectronic Science and Engineering, National University of Defense Technology, Changsha, Hunan 410073, People’s Republic of China) (Huazhong Institute of Optoelectronics Technology, Wuhan 430074, People’s Republic of China) (E-mail: zhengzhichao116@126.com)