Ground Alignment of Inertial Navigation System with the Aid of GPS Signals

Due to the poor observability of INS ground self alignment, only horizontal alignment is satisfied. This paper proposes using GPS double difference carrier phase as external reference to improve the observability of INS self alignment. Through observability analysis and computer simulation, it is demonstrated that the azimuth alignment is as quick as horizontal alignment, the accuracy of horizontal alignment is improved, and the gyros errors can be estimated quickly and precisely.

A fast and accurate initial alignment method for strapdown inertial navigation system on stationary base

In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system （SINS） is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS＇ s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.

Application of H_∞ filtering in the initial alignment of strapdown inertial navigation system

In this paper , the principle of H∞ filtering is discussed and H_∞ filter is constructed, which is used in the initial alignment of the strapdown inertial navigation systems(SINS). The error model of SINS is derived. By utilizing constructed H∞ filter, the filtering calculation to that system has been conducted. The simulation results of the misalignment angle are given under the condition of unknown noises. The results show that the process of alignment with H∞ filter is much faster and with excellent robustness.

Three-time rapid transfer alignment method of SINS/GPS navigation system of high-speed marine missile

The transfer alignment of SINS/GPS navigation system of a high-speed marine missile was investigated. With the help of the big acceleration of a high-speed missile, the transfer alignment was changed into a three-time alignment. The azimuth alignment was coarsely finished in 10s in the first time alignment, the horizontal alignment was accurately and rapidly finished in the second time alignment, and the azimuth alignment was accurately finished in the third time alignment. Because the second time alignment and the third time alignment were finished by GPS after the missile was launched, the horizontal alignment and the second azimuth alignment got rid of the influence of the warship body flexibility deforming. The precision and rapidity of the horizontal alignment were prominently increased due to the vertical launch of the marine missile with the big acceleration. Simulation verifies the effectiveness of the proposed alignment method.

Fast Compass Alignment for Strapdown Inertial Navigation System

Initial alignment is the precondition for strapdown inertial navigation system(SINS)to navigate.Its two important indexes are accuracy and rapidity,the accuracy of the initial alignment is directly related to the working accuracy of SINS,but in self-alignment,the two indexes are often contradictory.In view of the limitations of conventional data processing algorithms,a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed.By means of data storage,the same data is used in different stages of the initial alignment,which is beneficial to shorten the initial alignment time and improve the alignment accuracy.In order to verify the correctness of the compass algorithm based on stored data and repeated navigation calculation,the simulation experiment was done.In summary,when the computer performance is sufficiently high,the compass alignment method based on the stored data and the forward and reverse navigation calculation can effectively improve the alignment speed and improve the alignment accuracy.

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.

Transfer alignment of shipborne inertial-guided weapon systems

The transfer alignment problem of the shipborne weapon inertial navigation system （INS） is addressed. Specifically, two transfer alignment algorithms subjected to the ship motions induced by the waves are discussed. To consider the limited maneuver level performed by the ship, a new filter algorithm for transfer alignment methods using velocity and angular rate matching is first derived. And then an improved method using integrated velocity and integrated angular rate matching is introduced to reduce the effect of the ship body flexure. The simulation results show the feasibility and validity of the proposed transfer alignment algorithms.

Error Model of Rotary Ring Laser Gyro Inertial Navigation System

To improve the precision of inertial navigation system（INS） during long time operation,the rotation modulated technique（RMT） was employed to modulate the errorr of the inertial sensors into periodically varied signals,and,as a result,to suppress the divergence of INS errors.The principle of the RMT was introduced and the error propagating functions were derived from the rotary navigation equation.Effects of the measurement error for the rotation angle of the platform on the system precision were analyzed.The simulation and experimental results show that the precision of INS was ① dramatically improved with the use of the RMT,and ② hardly reduced when the measurement error for the rotation angle was in arc-second level.The study results offer a theoretical basis for engineering design of rotary INS.

Suppression of the G-sensitive drift of laser gyro in dual-axis rotational inertial navigation system

The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer can be averaged out,but the G-sensitive drifts of laser gyro cannot be averaged out by indexing.A 16-position rotational simulation experiment proves the G-sensitive drift will affect the long-term navigation error for the rotational INS quantitatively.The vibration coupling and asymmetric structure of the DRLG are the main errors.A new dithered mechanism and optimized DRLG is designed.The validity and efficiency of the optimized design are conformed by 1 g sinusoidal vibration experiments.An optimized inertial measurement unit(IMU)is formulated and measured experimentally.Laboratory and vehicle experimental results show that the divergence speed of longitude errors can be effectively slowed down in the optimized IMU.In long term independent navigation,the position accuracy of dual-axis rotational INS is improved close to 50%,and the G-sensitive drifts of laser gyro in the optimized IMU are less than 0.0002°/h.These results have important theoretical significance and practical value for improving the structural dynamic characteristics of DRLG INS,especially the highprecision inertial system.

The Performance Evaluation of the Integration of Inertial Navigation System and Global Navigation Satellite System with Analytic Constraints

The integration of GNSS （Global Navigation Satellite System） and INS （Inertial Navigation System） using IMU （Inertial Measurement Unit） is now widely used for MMS （Mobile Mapping System） and navigation applications to seamlessly determine position, velocity and attitude of the mobile platform. With low cost, small size, ligh weight and low power consumtion, the MEMS （Micro-Electro-Mechanical System） IMU and low cost GPS （Global Positioning System） receivers are now the trend in research and using for many applications. However, researchs in the literature indicated that the the performance of the low cost INS/GPS systems is still poor, particularly, in case of GNSS-noise environment. To overcome this problem, this research applies analytic contrains including non-holonomic constraint and zero velocity update in the data fusion engine such as Extended Kalman Filter to improve the performance of the system. The benefit of the proposed method will be demonstrated through experiments and data analysis.

Initial Alignment Technique for SINS of Vehicles in the Moving State

An initial alignment technique for the strapdown inertial navigation system (SINS) of vehicles in the moving state is researched. By selecting an odometer as the system’s external sensor, the mathematical model for the alignment in the moving state is established and the observability of the system is analyzed. The results show that the SINS can successfully achieve the precision alignment in 10 min when the vehicle is moving toward the prearranged place after its staying for several seconds to perform the coarse alignment. The precision of alignment can also be improved in the moving state compared with that in the static state.

Tightly-coupled model for INS/WSN integrated navigation based on Kalman filter

Aiming at the problem of poor observability of measurement information in the loosely-coupled integration of the inertial navigation system （INS） and the wireless sensor network （WSN）, this paper presents a tightly-coupled integration based on the Kalman filter （KF）. When the WSN is available, the difference between the distances from the blind node（BN） to the reference nodes （RNs） measured by the INS and those measured by the WSN are used as measurement information for the KF due to its better observability and independence, which can effectively improve the accuracy of the KF. Simulations show that the proposed approach reduces the mean error of the position by about 50% compared with loosely-coupled integration, while the mean error of the velocity is a little higher than that of loosely-coupled integration.

两种双矢量SINS粗对准方法大俯仰角适应性研究

大俯仰角下捷联惯导粗对准双矢量定姿中,不同矢量组合下,姿态角尤其是方位角对准精确度相差很大,必须慎重选择。对此,给出了2种最常用的粗对准矢量组合模式误差方程,对其主要误差影响因素进行分析。综合传感器误差,利用蒙特卡洛随机打靶方法对全姿态角下粗对准精确度进行仿真,并开展了80°俯仰角转台静态粗对准试验。转台试验中,在惯导陀螺误差约1°/h,加速度计误差约0.1mg情况下,第1种、第2种组合模式方位角粗对准最大误差值分别为20°、7.5°,第2种组合模式约为第1种的1/3;仿真测试中,在惯导陀螺误差约0.1°/h,加速度计误差约1mg,80°俯仰角下,第1种、第2种组合模式下方位角粗对准最大误差值分别为11°与2.2°,前者约为后者的5倍。仿真与试验结果表明,大俯仰角下矢量组合模式是影响惯导姿态角与姿态矩阵粗对准精确度的最主要因素。

Novel method of improving the alignment accuracy of SINS on revolving mounting base

In the process of initial alignment for a strapdown inertial navigation system （SINS） on a stationary base, the east gyro drift rate is an important factor affecting the alignment accuracy of the azimuth misalignment angle. When the Kalman filtering algorithm is adopted in initial alignment, it yields a constant error in the estimation of the azimuth misalignment angle because the east gyro drift rate cannot be estimated. To improve the alignment accuracy, a novel alignment method on revolving mounting base is proposed. The Kalman filtering algorithm of extending the measured values is studied. The theory of spectral condition number is utilized to analyze the degrees of observability of states. Simulation results show that the estimation accuracy of the azimuth misalignment angle is greatly improved through revolving mounting base, and the proposed method is efficient in initial alignment for a medium accurate SINS.

Research on SINS Alignment Algorithm Based on FIR Filters

An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method achieves the alignment by virtue of a cascade of low-pass FIR filters, which attenuate the disturbing acceleration and maintain the gravity vector. The aligning time rests with the orders of the FIR filter group, and the method is suitable for large initial misalignment case. An alignment scheme comprising a coarse phase by the IFBA method and a fine phase by a Kalman filter is presented. Both vehicle-based and ship-based alignment experiments were carried out. The results show that the proposed scheme converges much faster than the traditional method at no cost of precision and also works well under any large initial misalignment.

An INS/GNSS integrated navigation in GNSS denied environment using recurrent neural network

In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS,thereby obtaining a continuous,reliable and high-precision navigation solution.The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment.Subsequently,an experimental test on boat is also conducted to validate the performance of the method.The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal,as it outperforms extreme learning machine(ELM)and EKF by approximately 30%and 60%,respectively.

SINS in-Flight Alignment Using Quaternion Error Models

The widely used conventional linearized error models or perturbation models are not effective to represent the nonlinear characteristics of SINS error propagation with large attitude errors.Error equations in terms of quaternion error are derived,and extended Kalman filter techniques are used to solve the in-flight alignment problems.In the case of small attitude errors,the nonlinear models can be reduced to conventional phi-angle models.The simulation results show that the proposed error models may improve the performance of alignment.

Unscented Kalman filter for SINS alignment

In order to improve the filter accuracy for the nonlinear error model of strapdown inertial navigation system （SINS） alignment, Unscented Kalman Filter （UKF） is presented for simulation with stationary base and moving base of SINS alignment. Simulation results show the superior performance of this approach when compared with classical suboptimal techniques such as extended Kalman filter in cases of large initial misalignment. The UKF has good performance in case of small initial misalignment.

Rapid transfer alignment for SINS of carrier craft

In order to improve the survival ability and rapid response ability of the carrier craft,a new rapid transfer alignment method of the strapdown inertial navigation system（SINS） on a rocking base is put forward.In the method,the aircraft carrier does not need any form of movement.Meantime,interfering motions such as rolling,pitching,and yawing motions caused by sea waves are effectively used.Firstly,the deck flexure deformation model is made.Secondly,the state space model of transfer alignment is presented.Finally,the feasibility of this method is validated by the simulation.Simulation results show that the misalignment angle error can be estimated and reach an anticipated precision-0.2 mrad in 5 s,while the deck deformation angle error can be estimated and reach a better precision- 0.1 mrad in 20 s.