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

Space Technology Experiment and Climate Exploration(STECE) is a small satellite mission 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 function 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 precession 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 tracker's attitude measurement and presents a precession–nutation correction method based on attitude quaternion data. The periodic 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.     

A Nonlinear Tracker Using Attitude Measurements

The subject of this paper involves tracking the present position of a maneuvering aircraft as well as predicting its future position. A tracking filter is developed that uses aircraft attitude angles (yaw, pitch, roll) in addition to the usual radar measurements. Computer simulation of tracker performance when tracking violently maneuvering aircraft indicates that a dramatic improvement is obtained by using attitude information. The approach taken is to develop a 12-or 15-state extended Kalman filter that models both translational and rotational degrees of freedom. By measuring and estimating attitude it is possible to approximately determine the magnitude and direction of the force system acting on the vehicle and therefore determine vehicle linear acceleration. Knowledge of acceleration is then used to improve the estimate of present and future position of the vehicle being tracked. Simulation of a T-38 aircraft performing a 5 g turn indicates that the new tracker produces maximum trajectory prediction errors that are 36 percent of the errors experienced by more conventional trackers.     

A nonlinear helicopter tracker using attitude measurements

Extended-Kalman-filter-based trackers are discussed for maneuvering helicopters that use body angle and rotor tip-path-plane angle measurements in addition to the usual radar position measurements. Improvements were found in tracker performance when the body rotation and rotor tip-path-plane degrees of freedom were modeled within the extended Kalman filter. Tracker performance was further improved when measurements of body angles and rotor tip-path-plane angles were made available to the tracker     

Explicit formulas for two state Kalman, H/sub 2/ and H/sub /spl infin// target tracking filters

The continuous time, two state, target tracking problem is considered from the Kalman, H/sub 2/, and H/sub /spl infin// filter viewpoint. While previous treatments were numerical in nature, analytic transient responses and infinite horizon solutions with analytic performance expressions are presented here. Tracking indices, involving the maneuver and measurement uncertainties, are shown to have a role for both the steady state and transient responses. In addition, the H/sub /spl infin// tracker has a sensor index involving the performance bound and measurement uncertainty, which, along with the tracking index, plays a significant role in the H/sub /spl infin// tracker expressions. Analytical expressions for the probability of target escape, the probability that the target position will be outside the radar beamwidth (BW), are developed not only to compare the performance of various trackers, but also as a design tool to meet tracking specifications. Examples illustrate the performance of the target trackers as a function of the error gain upper bound.     

眼动分析技术及其在航空领域的应用进展

分析了眼动仪系统构成与原理,对几种典型眼动仪进行了性能比较。讨论了国内外眼动跟踪技术在航空领域的研究成果以及应用状况,对其应用研究特点进行了分析总结。最后,对在民用航空领域开展人为因素眼动系统研究的方法与前景进行了探讨和展望。     

Joint sensor registration and track-to-track fusion for distributed trackers

Sensor registration deals with the correction of registration errors and is an inherent problem in all multisensor tracking systems. Traditionally, it is viewed as a least squares or a maximum likelihood problem independent of the fusion problem. We formulate it as a Bayesian estimation problem where sensor registration and track-to-track fusion are treated as joint problems and provide solutions in cases 1) when sensor outputs (i.e., raw data) are available, and 2) when tracker outputs (i.e., tracks) are available. The solution to the latter problem is of particular significance in practical systems as band limited communication links render the transmission of raw data impractical and most of the practical fusion systems have to depend on tracker outputs rather than sensor outputs for fusion. We then show that, under linear Gaussian assumptions, the Bayesian approach leads to a registration solution based on equivalent measurements generated by geographically separated radar trackers. In addition, we show that equivalent measurements are a very effective way of handling sensor registration problem in clutter. Simulation results show that the proposed algorithm adequately estimates the biases, and the resulting central-level trucks are free of registration errors.     

Stability Criterion for a Hybrid Phase-Locked Loop Range Tracker

A currently tested high-performance electronic range tracker operating in a linear region and tracking a nearly stationary target can be modeled as a hybrid or gated phase-locked loop. A relationship for stability in this system is developed. The relationship is applicable to both Type I and Type II second-order hybrid phase-locked loop trackers.     

Star trackers for attitude determination

One problem comes to all spacecrafts using vector information. That is the problem of determining the attitude. This paper describes how the area of attitude determination instruments has evolved from simple pointing devices into the latest technology, which determines the attitude by utilizing a CCD camera and a powerful microcomputer. The instruments are called star trackers and they are capable of determining the attitude with an accuracy better than 1 arcsecond. The concept of the star tracker is explained. The obtainable accuracy is calculated, the numbers of stars to be included in the star catalogue are discussed and the acquisition of the initial attitude is explained. Finally the commercial market for star trackers is discussed     

Target tracking using infrared measurements and laser illumination

A missile target tracker is designed using a filter/correlator (with adaptive target shape identification) based on forward-looking infrared (FLIR) sensor measurements to track the center-of-intensity of the hardbody/plume combination, and another filter using Doppler and/or speckle information in the return from a low-power laser illuminator to estimate the offset between the intensity centroid and the hardbody center-of-mass. The Doppler information is shown to yield smaller bias and error variance from the tracker than the speckle information. Performance of trackers based on just Doppler or both Doppler and speckle information from the laser return is portrayed as a function of important parameters in the tracking environment     

A Kalman Tracker with a Simple Input Estimator

Two Kalman filter based schemes are proposed for tracking maneuvering targets. Both schemes use least squares to estimate a target's acceleration input vector and to update the tracker by this estimate. The first scheme is simpler and by an approximation to its input estimator the computation can be considerably reduced with insignificant performance degradation. The second scheme requires two Kalman filters and hence is more complex. However, since one of its two filters assumes input noise, it may outperform the first scheme when input noise is indeed present. A detector that compares the weighted norm of the estimated input vector to a threshold is used in each scheme. Its function is to guard against false updating of the trackers and to keep the error covariance small during constant velocity tracks. Simulation results for various target profiles are included. They show that in terms of tracking performance, both schemes are comparable. However, because of its computation simplicity, the first scheme is far superior.     

Model-based multifrequency array signal processing for low-angletracking

Tracking low-altitude targets over the sea is problematic because of interference between the direct and reflected signal. Standard monopulse trackers can experience large errors because of multipath maximum likelihood estimation (MLE) has been used to more accurately estimate the target height in the presence of multipath MLE is a model-fitting technique where the model parameters are chosen to maximize the likelihood function. It is shown that the type of observation model has a large effect on performance. Tracking performance is compared using three different observation models employing varying amounts of a priori information. Results are presented for different array sizes: eight and 32-element arrays and two-element subarrays typical of phase monopulse. Performance is compared with that of standard techniques such as Fourier beamforming and phase monopulse     

Data fusion of decentralized local tracker outputs

An approach for fusing offboard track-level data at a central fusion node is presented. The case where the offboard tracker continues to update its local track estimate with measurement and system dynamics models that are not necessarily linear is considered. An algorithm is developed to perform this fusion at a central node without having access to the offboard measurements, their noise statistics, or the location of the local estimator. The algorithm is based on an extension of results that were originally established for linear offboard trackers. A second goal of this work is to develop an inequality constraint for selecting the proper sampling interval for the incoming state estimates to the fusion node. This interval is selected to allow use of conventional Kalman filter algorithms at the fusion node without suffering error performance degradation due to processing a correlated sequence of track state estimates     

MULTISENSOR TRACKING SYSTEM WITH ATTITUDE MEASUREMENTS

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Tracking Accuracies with Position and Rate Measurements

Tracking accuracies for the radial component of motion are computed for a track-while-scan radar system which obtains position and rate data during the dwell time on a target These results will be of interest to persons developing trackers for pulse Doppler surveillance radars. The normalized accuracies, computed for a two state Kalman tracking filter with white noise maneuver capability, are shown to depend upon two parameters, r = 4?0/?aT2 and s = ?dT/?0. The symbols ?0 and ?d are the position and rate measurement accuracies, respectively, ?a is the standard deviation of the white noise maneuver process and T is the antenna scan time. The scalar tracking filter equations are derived and numerical results are presented. Lower steady state tracking errors plus the earlier attainment of steady state accuracies are the direct consequence of incorporating the rate measurements into the tracking filter.     

Track segment association, fine-step IMM and initialization with Doppler for improved track performance

In this work we present a new track segment association technique to improve track continuity in large-scale target tracking problems where track breakages are common. A representative airborne early warning (AEW) system scenario, which is a challenging environment due to highly maneuvering targets, close target formations, large measurement errors, long sampling intervals, and low detection probabilities, provides the motivation for the new technique. Previously, a tracker using the interacting multiple model (IMM) estimator combined with an assignment algorithm was shown to be more reliable than a conventional Kalman filter based approach in tracking similar targets but it still yielded track breakages due to the difficult environment. In order to combine the broken track segments and improve track continuity, a new track segment association algorithm using a discrete optimization approach is presented. Simulation results show that track segment association yields significant improvements in mean track life as well as in position, speed, and course rms errors. Also presented is a modified one-point initialization technique with range rate measurements, which are typically ignored by other initialization techniques, and a fine-step IMM estimator, which improves performance in the presence of long revisit intervals. Another aspect that is investigated is the benefit of "deep" (multiframe or N-dimensional, with N > 2) association, which is shown to yield significant benefit in reducing the number of false tracks.     

Differential GPS/inertial navigation approach/landing flight testresults

In November 1990, a differential GPS/inertial flight test was conducted to acquire a system performance database and demonstrate automatic landing using an integrated differential GPS/INS with barometric and radar altimeters. Flight test results obtained from postflight data analysis are presented. These results include characteristics of DGPS/inertial error, using a laser tracker as a reference. In addition, data are provided on the magnitude of the differential correlations and vertical channel performance with and without radar altimeter augmentation. Flight test results show one sigma DGPS/inertial horizontal errors of 9 ft and one sigma DGPS inertial vertical errors of 15 ft. Without selective availability effects, the differential corrections are less than 10 ft and are dominated by receiver unique errors over the time period of an approach. Therefore, the one sigma performance of the autonomous GPS (8-ft horizontal and 20-ft vertical) is very similar to the DGPS/inertial performance. Postprocessed results also demonstrate significant improvements in vertical channel performance when GPS/inertial is aided with radar altimeter along with a low-resolution terrain map     

PMHT: problems and some solutions

The probabilistic multihypothesis tracker (PMHT) is a target tracking algorithm of considerable theoretical elegance. In practice, its performance turns out to be at best similar to that of the probabilistic data association filter (PDAF); and since the implementation of the PDAF is less intense numerically the PMHT has been having a hard time finding acceptance. The PMHT's problems of nonadaptivity, narcissism, and over-hospitality to clutter are elicited in this work. The PMHT's main selling-point is its flexible and easily modifiable model, which we use to develop the "homothetic" PMHT; maneuver-based PMHTs, including those with separate and joint homothetic measurement models; a modified PMHT whose measurement/target association model is more similar to that of the PDAF; and PMHTs with eccentric and/or estimated measurement models. Ideally, "bottom line" would be a version of the PMHT with clear advantages over existing trackers. If the goal is of an accurate (in terms of mean square error (MSE)) track, then there are a number of versions for which this is available.     

Attitude and Oribit Estimation Using Stars and Landmarks

An extended Kalman filter is used to process line-of-sight measurements to stars and known landmarks providing a statistical indication of performance in estimating spacecraft attitude, orbital ephemeris, and the bias drift of a set of three strapdown gyros. The landmark measurements were assumed to have been taken from the imagery of an Earth-observing multispectral scanner. It is shown that filtering of these noisy measurements results in highly accurate estimates of the above parameters. Results are given showing the sensitivity of performance to various system parameters such as star tracker accuracy, errors in the knowledge of landmark position, and number of stars and landmarks processed.     

Noise effects on centroid tracker aim point estimation

An investigation of errors due to noise in centroid tracker aim-point estimation is presented. The centroid tracker discussed is similar to the tracker described by A.L. Gilbert et al. (1980). Simplifications to this algorithm were made so that the derived models would be consistent with the actual tracker algorithm. Two statistical models are derived which relate image noise effects to computation of the target centroid. The first model, the simplified aim-point error model, is derived by assuming that the probabilities of incorrectly classifying target and background pixels are equal. The second model, the extended aim-point error model, is derived by assuming that the probability of incorrectly classifying a target pixel can differ from the probability of incorrectly classifying a background pixel. These models are described and their mathematical implication is discussed. Simulation results which verify the models are presented