A method of coarse alignment for FOG based inertial platform system using rotation modulation

Navigation of Hypersonic vehicles in the radio frequency (RF) blackout area during atmospheric reentry is challenging as the vehicles can only use the inertial navigation system (INS) as autonomous navigation method in this area. In this paper, strapdown inertial navigation system (SINS) based on the Fiber Optic Gyroscope (FOG) is used for navigation in blackout area. However, without external navigation measurement, the errors of SINS caused by the FOG drift and accelerometer bias would cumulate with time and degrade navigation accuracy. To solve this problem, single axis rotation modulation along with the azimuth axis of the body frame is adopted. The Generic Hypersonic Vehicle (GHV) model designed by NASA Langley Research Center is used to build the reentry fight model which can generate navigation information for simulation. Through derivation the error equations of FOG SINS in the North-East-Down (NED) navigation frame, the principle of error compensation by rotation modulation can be well understood. The simulation results show that rotation modulation can effectively decrease the impact of inertial sensor drift and improve the navigation accuracy in blackout area.

Fiber optic gyroscopes (FOGs) are vital components for manned, unmanned, and autonomous platforms, as well as applications requiring extremely accurate data for stabilization, pointing, orientation of payloads, and navigation and control. FOG-based inertial systems also provide highly accurate data for all types of navigation, positioning, and georeferencing systems. Substantial improvements in the performance of FOGs and FOG-based inertial systems at KVH are directly related to advancements in the design and manufacture of optical fiber, as well as in manufacturing operations and signal processing. Open-loop FOGs, such as those developed and manufactured by KVH Industries, offer tactical-grade performance in a robust, small package. The success of KVH FOGs and FOG-based inertial systems is due to a series of key innovations including the development of proprietary D-shaped fiber with an elliptical core, as well as KVH's ThinFiber. KVH continually improves its FOG manufacturing processes and its signal processing, with the goal of improving accuracies across its entire FOG product line. KVH acquired its FOG capabilities, including its patented E·Core® fiber, when the company purchased the assets of Andrew Corporation's Sensor Products Group in 1997. E·Core fiber is unique in that the light-guiding fiber core — critical to the FOG's performance — is elliptically-shaped. The elliptical core results in an optical path with low loss and high polarization-maintaining ability. In 2011, KVH developed its ThinFiber, a 170-micron diameter dual acrylate-coated fiber that retains the full performance characteristics of E·Core fiber. ThinFiber has enabled the development of compact, high-performance open-loop FOGs, which are also used in a line of FOG-based inertial measurement units (IMUs) and inertial navigation systems (INS).

AlliedSignal Defense & Space Systems is ‘developing a miniaturized low-cost Inertial Measurement Unit (IMU) with tactical performance for missiles and munitions and for commercial applications. Many technology solutions are available that satisfy performance. This IMU design architecture ias established’ addressing cost as the primary performance parameter and then selecting the best technical performance solution to meet the cost goals. The, salient feature of the IMU is the use of two new inertial sensors designed primarily to significantly reduce cost through the use of micro-machined optoelectronic systems (MOES) for the gyro and’ micromachined electromechanical systems (MEMS) accelerometer technology. The SiMMA, Silicon Micro-Machined Accelerometer, provides the first product launch of tactical and inertial grade precision accelerometers. The SiFORS, Silicon Fiber-Optic Rotation Sensor, is an all silicon integrated optics gyro with fiber-optic sensing coil. ~The focus of theis, paper will be on the SiFORS gyro. In this paper we will be describe the design architecture and error budgets and present validating performance.’ 1. SiFORSTG IMU Introduction ’ AlliedSignal has developed a highly integrated very low cost Inertial Measurement Unit (IMU) based on Silicon integrated optics Fiber Optics Rotation Sensor’ (SiFORS) using MOES, Micro-machined OpticalElectronic Systems, and MEMS accelerometer technologies. The SiFORS IMU is environmentally robust and is currently, used in gun-hardened applications. The SiFORS lMU provides 600 Hz ,body rate and acceleration autopilot information and generates accurate. 100 Hi ‘measurements of angle (A@) and velocity (AV) for navigation applications. Its programmable data format and scaling capabilities allow a wide range of inertial navigation applications with minimum ‘design effort. Extensive performance 1 American Institute of Aeronautics and Astronautics 3 evaluations have been performed and the results are in close agreement with the predicted performance envelope. 1.1. Accelerometers in SiFORS IMU L Many solutions are available that satisfy the role of the accelerometer for all IMU applications and the. modular architecture of the’SiFORS lMU provides the flexibility for accelerometer selection. AlliedSignal’s RRA500 is a good accelerometer choice for the l-5 mg bias stability ‘range and the AlliedSignal SiMMATM, Silicon Micro-Machined Accelerometer, a. developing MEMS device, will soon be available in this performance range to further lower the IMU price. The gun-hardened system uses the Fndevco 7591 that provides, 10 mg performance after 12,000g launch shock. 1.2. Focus on SiFORS Rotation Sensor In this paper, we focus on the development and performance of the SiFORS, Silicon Fiber Optic Rotation Sensor.’ This sensor has a unique design employing the best features of both fiber optics and MOES processing. A key component of the SiFORS rotation sensor is the silicon integrated optics MultiFunction Chip (MFC), which provides the optical ( bench and low noise electronic detection capabilities for this Fiber Optic Gyroscope (FOG). An important feature of FOG technology is its performance scalability. The well understood FOG theory has facilitated performance predictions during ,.’ our SiFORS design and development phase. It also provides a low risk approach to developing performance’grade levels for various applications with the benefit being the lowest cost IMU for each performance grade. Since the entire MFC is fabricated using silicon technology, it can be produced with very high yield and is therefore ‘ideally suited for high volume, .low ‘. Copyright

At present the precision of fiber optic gyroscope (FOG) is so lower that it is necessary to analyze the performance of FOG and set up its drift error model to raise the precision. There are many noise source in FOG, these noise sources and environment intrusion cause many random error terms, such as bias instability, angular random walk,rate random walk and rate ramp. It is impossible to adopt general analytical method (such as calculating mean and covariance) to confirm these random errors. Now, the precision of FOG made in our country is low and to improve it cost high and is difficulty. So this paper improve the system precision by software in the error modeling and filtering of the FOG random drift. Now, the main method to minish the FOG random drift is Kalman filter. In this paper,the FOG drift data is processed by Kalman filter,and the effect of filtering is analyzed. The simulation result show that Kalman filter can minish the FOG random drift more simply and more efficiently. Because the Kalman filter is based on the steady time series model of FOG random drift, in this paper, FOG random drift data is validated to be a non-stationary time series, so the unsteady sample of FOG drift needs statistical test and corresponding pretreatment using stochastic signal processing methods, and then the mathematical model is establishing by time series analysis theory. It is proved that the random noise can be represented by a single equivalent ARMA(auto-regressive moving average) or ARIMA model that is simple to implement. The data pretreatment is made, the model is identified,the method of using long autoregression method to estimate the coefficients are studied. In the end, experimental modeling of the FOG random drift is carried out, the random noise of FOG is processed by using Kalman filter. Experimental results demonstrate that the performance of the filter is feasible and the model can reject the random noise of FOG.

Gyroscopes with high reliability and long lifespan are very important to the development of high quality space aerocrafts. In this article, various redundant configurations of fiber optic gyroscope (FOG) inertial measurement unit (IMU) is proposed. The reliability of these different configurations is studied. Moreover, this article analyses the error judgement rule when several FOGs work at the same time. Finally, the issues of measurement precision of different redundant configurations methods are discussed.

An inertial guidance system based on a fiber optic gyroscope (FOG) is an effective way to guide long-distance curved pipe jacking. However, environmental disturbances such as vibration, electromagnetism, and temperature will cause the FOG signal to generate significant random noise. The random noise will overwhelm the effective signal. Therefore, it is necessary to eliminate the random noise. This study proposes a hybrid de-noising method, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-lifting wavelet transform (LWT). Firstly, the FOG signal is extracted using a sliding window and decomposed by CEEMDAN to obtain the intrinsic modal function (IMF) with N different scales and one residual. Subsequently, the effective IMF components are selected according to the correlation coefficient between the IMF components and the FOG signal. Due to the low resolution of the CEEMDAN method for high-frequency components, the selected high-frequency IMF components are decomposed with lifting wavelet transform to increase the resolution of the signal. The detailed signals of the LWT decomposition are de-noised using the soft threshold de-noising method, and then the signal is reconstructed. Finally, pipe-jacking dynamic and environmental interference experiments were conducted to verify the effectiveness of the CEEMDAN-LWT de-noising method. The de-noising effect of the proposed method was evaluated by SNR, RMSE, and Deviation and compared with the CEEMDAN and LWT de-noising methods. The results show that the CEEMDAN-LWT de-noising method has the best de-noising effect with good adaptivity and high accuracy. The navigation results of the pipe-jacking attitude before and after de-noising were compared and analyzed in the environmental interference experiment. The results show that the absolute error of the pipe-jacking pitch, roll, and heading angles is reduced by 39.86%, 59.45%, and 14.29% after de-noising. The maximum relative error of the pitch angle is improved from -0.74% to -0.44%, the roll angle is improved from 2.07% to 0.79%, and the heading angle is improved from -0.07% to -0.06%. Therefore, the CEEMDAN-LWT method can effectively suppress the random errors of the FOG signal caused by the environment and improve the measurement accuracy of the pipe-jacking attitude.

Rotation modulation technology could effectively improve the accuracy of the inertial navigation system (INS) by compensating for the biases of the inertial sensors automatically. However, the carrier angular motion and rotation control error could reduce the rotation modulation effect and then decrease the navigation accuracy. To address this problem, for the single-axis rotation INS, a novel rotation control scheme is presented. The control scheme employs the fiber optic gyros to control the inertial measurement unit (IMU) rotation angular velocity so that the INS with both rotation modulation and azimuth motion insulation functions. Furthermore, in order to reduce the control error, this study adopts two ways: optimizing the control strategy and shortening the delay time. The former way is to control the IMU rotating about the z-axis of the platform frame with respect to the navigation frame, rather than the up-axis of the navigation frame. The latter way is to apply interrupt mode rather than inquiry mode to complete the data transfer between the navigation and the control processors. The simulation and experimental results demonstrate that: the proposed method would not only realize the rotation modulation of the biases of the inertial sensors, but also achieve the insulation of the azimuth motion. The steady-state control error of the control system is less than 10" and the overshoot control error is less than 50". Compared to the traditional SRINS, the navigation position error in the single-axis rotation/azimuth-motion insulation INS could reduce 50% in some navigation application.

High-sensitivity uniaxial opto-mechanical accelerometers provide very accurate linear acceleration measurements. In addition, an array of at least six accelerometers allows the estimation of linear and angular accelerations and becomes a gyro-free inertial navigation system. In this paper, we analyze the performance of such systems considering opto-mechanical accelerometers with different sensitivities and bandwidths. In the six-accelerometer configuration adopted here, the angular acceleration is estimated using a linear combination of accelerometers' read-outs. The linear acceleration is estimated similarly but requires a correcting term that includes angular velocities. Accelerometers' colored noise from experimental data is used to derive, analytically and through simulations, the performance of the inertial sensor. Results for six accelerometers, separated by 0.5 m in a cube configuration show noise levels of 10-7 m s-2 and 10-5 m s-2 (in Allan deviation) for time scales of one second for the low-frequency (Hz) and high-frequency (kHz) opto-mechanical accelerometers, respectively. The Allan deviation for the angular velocity at one second is 10-5 rad s-1 and 5×10-4 rad s-1. Compared to other technologies such as MEMS-based inertial sensors and optical gyroscopes, the high-frequency opto-mechanical accelerometer exhibits better performance than tactical-grade MEMS for time scales shorter than 10 s. For angular velocity, it is only superior for time scales less than a few seconds. The linear acceleration of the low-frequency accelerometer outperforms the MEMS for time scales up to 300 s and for angular velocity only for a few seconds. Fiber optical gyroscopes are orders of magnitude better than the high- and low-frequency accelerometers in gyro-free configurations. However, when considering the theoretical thermal noise limit of the low-frequency opto-mechanical accelerometer, 5×10-11 m s-2, linear acceleration noise is orders of magnitude lower than MEMS navigation systems. Angular velocity precision is around 10-10 rad s-1 at one second and 5×10-7 rad s-1 at one hour, which is comparable to fiber optical gyroscopes. While experimental validation is yet not available, the results shown here indicate the potential of opto-mechanical accelerometers as gyro-free inertial navigation sensors, provided the fundamental noise limit of the accelerometer is reached, and technical limitations such as misalignments and initial conditions errors are well controlled.

Efficient hybrid Kalman filter for denoising fiber optic gyroscope signal

Six-degree of freedom (DOF) inertial measurement units (IMUs) are widely used for attitude estimation. However, such systems' accuracy is limited by the accuracy of calibration of bias, scale factors, and non-orthogonality of sensor measurements. This paper reports a stable adaptive estimator of measurement bias in six-DOF IMUs and preliminary simulation results employing a commercially available IMU comprising a 3-axis fiber optic gyroscope (FOG) with a 3-axis micro-electro-mechanical systems (MEMS) accelerometer. A stability proof of the adaptive estimator and preliminary numerical simulation results are reported. The simulation results for a rotating IMU configuration are promising, and further experimental evaluation and extension of the algorithm for the case of a translating IMU configuration typically found on moving robotic vehicles are needed.

The scheme based on the inertial measurement of measurement while drilling (MWD) is the developing direction of MWD, but the gyroscope is the bottleneck which arbitrarily restricts the application of the scheme. This paper discusses on the Inertial Measurement Unit (IMU) consisting of three fiber optic gyroscope and three accelerometers, as well as the measurement while drilling algorithm based on the IMU. In the structural design of this system, IMU rotating framework is utilized to modulate the output signal of the FOG, which will reduce the constant drift of gyroscopes and improve the accuracy of the attitude angle and well trajectory. What's more, the paper simulates the MWD algorithm with and without the rotating modulation, and proves the accuracy and effectiveness of the algorithm with the rotating modulation.

Aiming at the interferences caused by vibrations on the target monitoring system of satellite platforms, an experimental system of optical–mechanical–electrical joint image stabilization based on inertial sensors and piezoelectric fast mirrors was studied. First of all, the data from the fiber optic gyroscope and the detector are combined and processed. After that, the predicted intentional velocity is subtracted from the real-time gyroscope data, and the vibration displacement is obtained using an integral. The feedback amount is calculated using the processor according to the vibration displacement, the piezoelectric fast mirror is controlled to compensate the vibration interferences, and the purpose of stabilizing the images is achieved. The experimental results show that under a vibration interference of 300μrad/s, the image stabilization control frequency of the system reaches 500 Hz, the relative error between image frames is better than 3μrad, and the intra-frame stabilization performance of the detector meets the requirements on stabilized image and target detection for space targets on the star-carrying platform.

Inertial navigation provides a unique ability to know where one has been, where one is currently, and where one is going, given only a starting position. The laws of physics permit the sensing of dynamic motion without external information, making inertial systems impervious to jamming, masking, or spoofing. Measurements of six degrees of freedom are required - three linear accelerations, and three angular rates - to fully propagate the velocity, position, and orientation of the system. The first inertial sensors are traced to the early 19th century and specialized inertial guidance systems appeared in the 1940s, yet inertial navigation systems did not become commonplace until the 1960s. This is largely due to the fact that requirements for navigation accuracy inertial sensors - accelerometers and gyroscopes - are very challenging. In the past fifty years, significant evolutionary and revolutionary changes have taken place in the designs of inertial sensors and systems. These include the progression from fluid-filled to dry instruments and the transition from mechanically complex stabilized inertial platforms to computationally intensive strapdown systems. Gyroscopes have evolved from large mechanical devices to highly refined precision mechanical sensors. Optical rotation sensors such as the ring laser gyro and the fiber optic gyro have enabled new system designs and capabilities. Coriolis vibratory gyroscopes such as the hemispherical resonator gyro are capable of extreme accuracy and reliability; new opportunities for miniaturizing these types of sensors will lead to new classes of accuracy for inertial navigation systems. Advanced gyroscope technologies such as the nuclear magnetic resonance gyroscope which uses atomic spin to detect rotation have already been demonstrated to achieve navigation accuracy requirements. Cold atom technologies may also provide the opportunity for very high accuracy accelerometers and gyroscopes in the future. Inertial navigation technologies and applications of the past, present, and future are discussed.

Self-alignment of full skewed RSINS: Observability analysis and full-observable Kalman filter

Research at the University of Michigan's Mobile Robotics Lab aims at the development of an accurate Proprioceptive (i.e. without external references) Position Estimation (PPE) system for planetary rovers. Much like other PPE systems, ours uses an Inertial Measurement Unit (IMU) comprising three Fibre Optic Gyroscopes (FOGs) and a two-axes accelerometer, as well as odometry based on wheel encoders. Our PPE system combines data based on expert rules that implement our in-depth understanding of each sensor modality's behaviour under different driving and environmental conditions. Since our system also uses Fuzzy Logic operations in conjunction with the Expert Rules for finer gradation, we call it Fuzzy Logic Expert navigation (FLEXnav) PPE system. The paper presents detailed experimental results obtained with our FLEXnav system integrated with our planetary rover clone, Fluffy and operating in a Mars-like environment. In addition, we compare the results of our FLEXnav system with the results obtained from a conventional Kalman Filter (KF). The paper also introduces new methods for wheel slippage detection and correction, along with comprehensive experimental results.