Progress on error propagation and correction of long-range rockets in disturbing gravity field

Disturbing gravity field is becoming an important factor leading to impact error of long-range rockets. In this paper, the influence mechanism of deflection of the vertical and spatial disturbing gravity on inertial navigation and guidance system are firstly introduced, respectively. Then, the navigation error propagation methods due to disturbing gravity field are reviewed. The fast assignment models of disturbing gravity field, which are available for compensating navigation errors in engineering, are also summarized. After that, the unpowered trajectory error propagation methods and the corresponding guidance correction strategies, as well as potential directions for future efforts, are discussed.

Autonomous Landing of Micro Unmanned Aerial Vehicles with Landing-Assistive Platform and Robust Spherical Object Detection

Autonomous unmanned aerial vehicle (UAV) landing can be useful in multiple applications. Precise landing is a difficult task because of the significant navigation errors of the global positioning system (GPS). To overcome these errors and to realize precise landing control, various sensors have been installed on UAVs. However, this approach can be challenging for micro UAVs (MAVs) because strong thrust forces are required to carry multiple sensors. In this study, a new autonomous MAV landing system is proposed, in which a landing platform actively assists vehicle landing. In addition to the vision system of the UAV, a camera was installed on the platform to precisely control the MAV near the landing area. The platform was also designed with various types of equipment to assist the MAV in searching, approaching, alignment, and landing. Furthermore, a novel algorithm was developed for robust spherical object detection under different illumination conditions. To validate the proposed landing system and detection algorithm, 80 flight experiments were conducted using a DJI TELLO drone, which successfully landed on the platform in every trial with a small landing position average error of 2.7 cm.

Modified Sage-Husa Adaptive Kalman Filter-Based SINS/DVL Integrated Navigation System for AUV

This paper presents a modified Sage-Husa adaptive Kalman filter-based SINS/DVL integrated navigation system for the autonomous underwater vehicle (AUV), where DVL is employed to correct the navigation errors of SINS that accumulate over time. When negative definite items are large enough, different from the positive definiteness of noise matrices which cannot be guaranteed for the conventional Sage-Husa adaptive Kalman filter, the proposed modified Sage-Husa adaptive Kalman filter deletes the negative definite items of adaptive update laws of the noise matrix to ensure the convergence of the Sage-Husa adaptive Kalman filter. In other words, this method sacrifices some filtering precision to ensure the stability of the filter. The simulation tests are implemented to verify that expected navigation accuracy for AUV can be obtained using the proposed modified Sage-Husa adaptive Kalman filter.

The Integration of Rotary MEMS INS and GNSS with Artificial Neural Networks

The rotary INS (inertial navigation system) has been applied to compensate the navigation errors of the MEMS (micro-electro-mechanical-systems) INS recently. In such system, the PVA (position, velocity, and attitude) errors can be compensated through IMU (inertial measurement unit) carouseling. However, the navigation errors are only partially compensated due to the intrinsic property of the inertial system and the randomness of the IMU errors. In this paper, we present an integrated rotary MEMS INS/GNSS (global navigation satellite systems) system based on the ANN (artificial neural networks) technique. The ANFIS (adaptive neuro-fuzzy inference system) is applied to eliminate the residual PV (position and velocity) errors of the rotary MEMS INS during GNSS outages. A cascaded velocity-position structure is designed to recognize the pattern of the rotary MEMS INS PV errors and to reduce them of the rotary inertial system in standalone mode. The road tests are conducted with artificial GNSS outages to evaluate the ability of the integrated system to predict the PV errors. Compared to the position errors of the integrated rotary INS/GNSS system based on an EKF (extended Kalman filtering), they are reduced by 79.98% in the proposed system.

Temperature Hysteresis Mechanism and Compensation of Quartz Flexible Accelerometer in Aerial Inertial Navigation System

Strap-down inertial navigation systems (INSs) with quartz flexible accelerometers (QFAs) are widely used in many conditions, particularly in aerial vehicles. Temperature is one of the significant issues impacting the performance of INS. The variation and the gradient of temperature are complex under aerial conditions, which severely degrades the navigation performance of INS. Previous work has indicated that parts of navigation errors could be restrained by simple temperature compensation of QFA. However, the temperature hysteresis of the accelerometer is seldom considered in INS. In this paper, the temperature hysteresis mechanism of QFA and the compensation method would be analyzed. Based on the fundamental model, a comprehensive temperature hysteresis model is proposed and the parameters in this model were derived through a temperature cycling test. Furthermore, the comparative experiments in the laboratory were executed to refine the temperature hysteresis model and to verify the effectiveness of the new compensation method. Applying the temperature hysteresis compensation in flight condition, the result shows that the position error (CEP) is restrained from 1.54 nmile/h to 1.29 nmile/h. The proposed temperature hysteresis compensation method improves the performance of INS effectively and feasibly, which could be promoted to other applications of INS in similar temperature changing environment correspondingly.

Relationship Between the Accuracy of Acetabular Cup Angle and Body Mass Index in Posterolateral Total Hip Arthroplasty With CT-Based Navigation: A Retrospective Case-Control Study

Background: Precise acetabular cup placement is essential for successful total hip arthroplasty (THA). In obese patients, its accuracy is often difficult to achieve because of the thickness of the soft tissues. This study aimed to determine the relationship between the accuracy of acetabular cup angle and body mass index (BMI) in posterolateral THA using the computed tomography-based navigation (CT-navi) system.Methods: We retrospectively reviewed 145 consecutive primary THAs using the CT-navi system between January 2015 and January 2018. All surgeries were performed using cementless cups employing the posterolateral approach with the patient in the decubitus position. We compared the radiographic inclination and anteversion obtained from the angle displayed on the CT-navi screen with those measured by the postoperative CT using the three-dimensional templating software. We evaluated the relationship between the extent of errors and correlation with BMI. Statistical analyses were performed using the Student’s t-test and Spearman’s rank coefficient test.Results: In non-overweight patients (BMI < 25, 88 hips), the mean navigation errors for inclination were 2.8 ± 2.2° and for anteversion were 2.6 ± 2.3°. Meanwhile, in overweight patients (BMI ≥ 25, 57 hips), the mean navigation errors were 2.6 ± 2.4° for inclination and 2.4 ± 2.4° for anteversion. We found no significant difference between overweight and non-overweight patients in both inclination and anteversion. The Spearman’s rank correlation coefficients were -0.04 for inclination and -0.11 for anteversion, showing no correlation between the extent of errors and BMI.Conclusions: In posterolateral THA, CT-navi can aid the precise placement of the acetabular cup irrespective of a patient’s BMI.Trial registration: This trial was retrospectively registered and approved by the institutional ethics committee of Teikyo University. The registration number is 17-190, and the date of approval was March 1, 2018. URL of trial registry is: https://www.teikyo-u.ac.jp/application/files/7015/8432/1341/2016_all_syounin_1.pdf