ENGINEERING REALIZATION OF MULTIPLE ANTENNA GPS IN ATTITUDE DETERMINATION INTEGRATED SYSTEM

A multiple antenna GPS system integrated with MEMS-based INS is proposed by data fusion. The system is applied to attitude determination due to its high accuracy, the high output rate, low latency, quick initialization, and good robustness and redundancy. The mathematical method for realizing the system is given. The system can provide attitude and other navigation information even without GPS measurement for a period of time. Experimental results show that, under the condition of 200 Hz, the attitude, the position, the velocity, the acceleration, and the angular rate can achieve 0. 08°/s, 1.5 m, 0. 1 m/s, 0. 12 m/s^2 and 0. 1°/s.

Neural Network-based GPS/INS Integrated System for Spacecraft Attitude Determination

Global Positioning System （GPS） /Inertial Navigation System （INS） integrated system is continuously gaining research interests in many positioning and navigation fields. Kalman filtering-based integrated algorithm has some drawbacks on stability, computation load, robustness, and system observability performances. Based on neural network technology, a new GPS/INS integration filtering algorithm is studied for an integration scheme of the attitude determination GPS/INS integrated navigation system. Through some theoretic analysis, this algorithm not only has good estimation performance, but also has better robustness to the system model and noise than the traditional Kalman algorithm. To assess the performance of the proposed integrated model more deeply, some simulation is done to compare with the traditional Kalman filter model. The results indicate that the proposed model provides a significant improvement in some performance, such as accuracy, stability, robustness, and so on.

Design and application of single-antenna GPS/accelerometers attitude determination system

In view of the problem that the current single-antenna GPS attitude determination system can only determine the body attitude when the sideslip angle is zero and the multiantenna GPS/SINS integrated navigation system is of large volume, high cost, and complex structure, this approach is presented to determine the attitude based on vector space with single-antenna GPS and accelerometers in the micro inertial measurement unit （MIMU）. It can provide real-time and accurate attitude information. Subsequently, the single-antenna GPS/SINS integrated navigation system is designed based on the combination of position, velocity, and attitude. Finally the semi- physical simulations of single-antenna GPS attitude determination system and single-antenna GPS/SINS integrated navigation system are carried out. The simulation results, based on measured data, show that the single-antenna GPS/SINS system can provide more accurate navigation information compared to the GPS/SINS system, based on the combination of position and velocity. Furthermore, the single-antenna GPS/SINS system is characteristic of lower cost and simpler structure. It provides the basis for the application of a single-antenna GPS/SINS integrated navigation system in a micro aerial vehicle （MAV）.

Comparison of attitude determination approaches using multiple Global Positioning System (GPS) antennas

GPS-based attitude system is an important research field, since it is a valuable technique for the attitude determination of platforms. There exist two classes approaches for attitude determination using the GPS. The one determines attitude via baseline estimates in two frames, the other one solves for attitude by incorporating the attitude parameters directly into the GPS measurements. However, comparisons between these two classes approaches have been unexplored. First of all, two algorithms are introduced in detail which on behalf of these two kinds of approaches. Then we present numerical simulations demonstrating the performance of our algorithms and provide a comparison evaluating.

Estimation of Quaternion Motion for GPS-Based Attitude Determination Using the Extended Kalman Filter

In this paper,the Global Positioning System(GPS)interferometer provides the preliminarily computed quaternions,which are then employed as the measurement of the extended Kalman filter(EKF)for the attitude determination system.The estimated quaternion elements from the EKF output with noticeably improved precision can be converted to the Euler angles for navigation applications.The aim of the study is twofold.Firstly,the GPS-based computed quaternion vector is utilized to avoid the singularity problem.Secondly,the quaternion estimator based on the EKF is adopted to improve the estimation accuracy.Determination of the unknown baseline vector between the antennas sits at the heart of GPS-based attitude determination.Although utilization of the carrier phase observables enables the relative positioning to achieve centimeter level accuracy,however,the quaternion elements derived from the GPS interferometer are inherently noisy.This is due to the fact that the baseline vectors estimated by the least-squares method are based on the raw double-differenced measurements.Construction of the transformation matrix is accessible according to the estimate of baseline vectors and thereafter the computed quaternion elements can be derived.Using the Euler angle method,the process becomes meaningless when the angles are at 90where the singularity problem occurs.A good alternative is the quaternion approach,which possesses advantages over the equivalent Euler angle based transformation since they apply to all attitudes.Simulation results on the attitude estimation performance based on the proposed method will be presented and compared to the conventional method.The results presented in this paper elucidate the superiority of proposed algorithm.

Complementary Kalman Filter as a Baseline Vector Estimator for GPS-Based Attitude Determination

The Global Positioning System(GPS)offers the interferometer for attitude determination by processing the carrier phase observables.By using carrier phase observables,the relative positioning is obtained in centimeter level.GPS interferometry has been firstly used in precise static relative positioning,and thereafter in kinematic positioning.The carrier phase differential GPS based on interferometer principles can solve for the antenna baseline vector,defined as the vector between the antenna designated master and one of the slave antennas,connected to a rigid body.Determining the unknown baseline vectors between the antennas sits at the heart of GPS-based attitude determination.The conventional solution of the baseline vectors based on least-squares approach is inherently noisy,which results in the noisy attitude solutions.In this article,the complementary Kalman filter(CKF)is employed for solving the baseline vector in the attitude determination mechanism to improve the performance,where the receiver-satellite double differenced observable was utilized as the measurement.By using the carrier phase observables,the relative positioning is obtained in centimeter level.Employing the CKF provides several advantages,such as accuracy improvement,reliability enhancement,and real-time assurance.Simulation results based on the conventional method where the least-squares approach is involved,and the proposed method where the CKF is involved are compared and discussed.

Application of Mean Field Annealing Algorithms to GPS-Based Attitude Determination

This paper researches the attitude determination of a body based on GPScarrier phase measurement, and the algorithms used is the mean field annealing neuralnetwork(MFANN), which has the advantages of high accuracy and rapidity. The MFANN approach is acombination of the competitive Hopfield neural network and the stochastic simulated annealingtechnique, which is efficacious in resolving the optimal attitude determination. Firstly, thefundamental principle of GPS attitude determination is described, then a test platform of attitudedetermination is set up, and the MFANN algorithm is verified to resolve integer ambiguity andazimuth angles. Lastly, the experimental example is presented by means of MFANN, and it shows thatthis method is effective.

Design on a Multi-Sensor Integrated Attitude Determination System for Small UAVs

This paper discusses the design and implementation of a low cost multi-sensor integrated attitude determination system for small unmanned aerial vehicles( UAVs),which uses strapdown inertial navigation system( SINS) based on micro electromechanical system( MEMS) inertial sensors,commercial GPS receiver,and 3-axis magnetometer.MEMS-SINS initial attitude determination cannot be well performed for the reason that the MEMS inertial sensors biases are time-varying and poor repeatability,therefore in this paper the magnetometer and inclinometer are used to assist the MEMS-SINS initial attitude determination and MEMS inertial sensors field calibration.Furthermore,the attitude determination algorithms are presented to estimate the full attitude during GPS signal outage and non-accelerating situation.Additionally,the attitude information estimation results are compared with the reference of the non-magnetic marble platform and 3-axis turntable.Then the attitude estimation precision satisfies the requirement of attitude measurement for small UAVs during GPS signal outage and availability.Finally,the small UAV autonomous flight test results show that the low cost and real-time attitude determination system can yield continuous,reliable and effective attitude information for small UAVs.

Estimator-Based GPS Attitude and Angular Velocity Determination

In this paper,the estimator-based Global Positioning System(GPS)attitude and angular velocity determination is presented.Outputs of the attitude estimator include the attitude angles and attitude rates or body angular velocities,depending on the design of estimator.Traditionally as a position,velocity and time sensor,the GPS also offers a free attitude-determination interferometer.GPS research and applications to the field of attitude determination using carrier phase or Doppler measurement has been extensively conducted.The rawattitude solution using the interferometry technique based on the least-squares approach is inherently noisy.The estimator such as the Kalman filter(KF)or extended Kalman filter(EKF)can be incorporated into the GPS interferometer,potentially providing several advantages,such as accuracy improvement,reliability enhancement,and real-time characteristics.Three estimator-based approaches are investigated for performance comparison,including(1)KF with measurement involving attitude angles only;(2)EKF with measurements based on attitude angles only;(3)EKF with measurements involving both attitude angles and body angular rates.The assistance from body mounted gyroscopes,if available,can be utilized as the measurements for further performance improvement,especially useful for the case of signal-challenged environment,such as the GPS outages.Modeling of the dynamic process involving the body angular rates and derivation of the related algorithm will be presented.Simulation results for various estimator-based approaches are conducted;performance comparison is presented for the case of GPS outages.

Determination of Vessel Attitudes Using GPS

With the development of GPS carrier wave phase technology, it becomes possible that the height accuracy of centimeter level is got by GPS RTK technology. Vessel attitudes are very important parameters in marine survey. In this paper, they were determined by 4 GPS receivers. At the same time, the arithmetic and procedure of vessel attitude determining were given. Based on an experiment, some useful conclusions were obtained and the corresponding methods were put forward to improve the accuracy.

IDENTIFICATION OF GYRO DRIFTS UNDER THREE AXIS ATTITUDE COUPLING

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ATTITUDE RATE ESTIMATION BY GPS DOPPLER SIGNAL PROCESSING

A method is presented for near-Earth spacecraft or aviation vehicle's attitude rate estimation by using relative Doppler frequency shift; of the Global Positioning System (GPS) carrier. It comprises two GPS receiving antennas, a signal processing circuit and an algorithm. The whole system is relatively simple, the cost and weight, as well as power consumption, are very low.

An improved quaternion Gauss–Newton algorithm for attitude determination using magnetometer and accelerometer

For the vector attitude determination, the traditional optimal algorithms which are based on quaternion estimator（QUEST） measurement noise model are complicated for just two observations. In our application, the magnetometer and accelerometer are not two comparable kinds of sensors and both are not small field-of-view sensors as well. So in this paper a new unit measurement model is derived. According to the Wahba problem, the optimal weights for each measurement are obtained by the error variance researches. Then an improved quaternion Gauss–Newton method is presented and adopted to acquire attitude. Eventually, simulation results and experimental validation employed to test the proposed method demonstrate the usefulness of the improved algorithm.

Hybrid analytical resolution approach based on ambiguity function for attitude determination

When satellite navigation receivers are equipped with multiple antennas, they can deliver attitude information. In previous researches, carrier phase differencing measurement equations were built in the earth-centered, earth-fixed (ECEF) co- ordinate, and attitude angles could be obtained through the rotation matrix between the body frame (BF) and the local level frame (LLF). Different from the conventional methods, a hybrid algorithm is presented to resolve attitude parameters utilizing the single differencing (SD) carrier phase equations established in LLF. Assuming that the cycle integer ambiguity is known, the measure- ment equations have attitude analytical resolutions by using simultaneous single difference equations for two in-view satellites. In addition, the algorithm is capable of reducing the search integer space into countable 2D discrete points and the ambiguity function method (AFM) resolves the ambiguity function within the analytical solutions space. In the case of frequency division multiple access (FDMA) for the Russian Global Orbiting Navigation Satellite System (GLONASS), a receiver clock bias estimation is employed to evaluate its carrier phase. An evaluating variable and a weighted factor are introduced to assess the integer ambiguity initialization. By static and dynamic ground experiments, the results show that the proposed approach is effective, with enough accuracy and low computation. It can satisfy attitude determination in cases of GPS alone and combined with GLONASS.

DOA estimation for attitude determination on communication satellites

In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival （DOA） estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system （GPS） attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit （LEO） satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio （SNR） with DOA estimation.

Interlaced optimal-REQUEST and unscented Kalman filtering for attitude determination

Aimed at low accuracy of attitude determination because of using low-cost components which may result in non-linearity in integrated attitude determination systems, a novel attitude determination algorithm using vector observations and gyro measurements is presented. The various features of the unscented Kalman filter （UKF） and optimal-REQUEST （quaternion estimator） algorithms are introduced for attitude determination. An interlaced filtering method is presented for the attitude determination of nano-spacecraft by setting the quaternion as the attitude representation, using the UKF and optimal-REQUEST to estimate the gyro drifts and the quaternion, respectively. The optimal-REQUEST and UKF are not isolated from each other. When the optimal-REQUEST algorithm estimates the attitude quaternion, the gyro drifts are estimated by the UKF algorithm synchronously by using the estimated attitude quaternion. Furthermore, the speed of attitude determination is improved by setting the state dimension to three. Experimental results show that the presented method has higher performance in attitude determination compared to the UKF algorithm and the traditional interlaced filtering method and can estimate the gyro drifts quickly.

Attitude Determination for MAVs Using a Kalman Filter

This paper presents a Kalman filter to effectively and economically determine the Euler angles for micro aerial vehicles （MAVs）, whose size and payload are severely limited. The filter uses data from a series of micro-electro mechanical system sensors to determine the selected 3 variables of the direction cosine matrix and the bias of the rate gyro sensors as state elements in a dynamic model, with the gravitational acceleration to build a measurement model. For high speed maneuvers, rigid motion equations are used to correct the measurements of the gravitational acceleration. The filter is designed to automatically tune its gain based on the dynamic system state. Simulations indicate that the Euler angles can be determined with standard deviations less than 3°. The algorithm was successfully implemented in a miniature attitude measurement system suitable for MAVs. Aerobatic flights show that the attitude determination algorithm works effectively. The attitude determination algorithm is effective and economical, and can also be applied to bionic robofishs and land vehicles, whose size and payload are also greatly limited.

GPS dynamic cycle slip detection and correction with baseline constraint

When the cycle slips take place in the attitude determination of a moving platform, the precision of the attitude will be impaired badly. A method of cycle slip detection and correction is proposed, which is suitable to the dynamic measurement using GPS carrier phase： the cycle slips detection is first achieved by triple difference observables, then the cycle slips correction is performed with baseline length constraint. The simulation results show that the proposed method is effective to the dynamic cycle slips problem.

Precession–nutation correction for star tracker attitude measurement of STECE satellite

Space Technology Experiment and Climate Exploration （STECE） is a small satellite mis- sion of China for space technology experiment and climate exploration. A new test star tracker and one ASTRO 10 star tracker have been loaded on the STECE satellite to test the new star tracker＇s measurement performance. However, there is no autonomous precession nutation correction func- tion for the test star tracker, which causes an apparent periodic deflection in the inter-boresight angle between the two star trackers with respect to each other of up to - 500 arcsec, so the preces- sion and nutation effect needs to be considered while assessing the test star tracker. This paper researches on the precession-nutation correction for the test star traeker＇s attitude measurement and presents a precession-nutation correction method based on attitude quaternion data. The peri- odic deflection of the inter-boresight angle between the two star trackers has been greatly eliminated after the precession and nutation of the test star tracker＇s attitude data have been corrected by the proposed method and the validity of the proposed algorithm has been demonstrated. The in-flight accuracy of the test star tracker has been assessed like attitude noise and low-frequency errors after the precession-nutation correction.

Low-frequency Periodic Error Identification and Compensation for Star Tracker Attitude Measurement

The low-frequency periodic error of star tracker is one of the most critical problems for high-accuracy satellite attitude determination.In this paper an approach is proposed to identify and compensate the low-frequency periodic error for star tracker in attitude measurement.The analytical expression between the estimated gyro drift and the low-frequency periodic error of star tracker is derived firstly.And then the low-frequency periodic error,which can be expressed by Fourier series,is identified by the frequency spectrum of the estimated gyro drift according to the solution of the first step.Furthermore,the compensated model of the low-frequency periodic error is established based on the identified parameters to improve the attitude determination accuracy.Finally,promising simulated experimental results demonstrate the validity and effectiveness of the proposed method.The periodic error for attitude determination is eliminated basically and the estimation precision is improved greatly.