Abstract: Methods, non-transitory computer readable medium and devices that initiating determination of navigation with an initial heading while in motion and without waiting for a stationary phase. Ongoing position-dependent data and/or velocity-dependent data of an object is/are received from a Global Navigation Satellite System (GNSS) receiver system or a position fixing system and from an inertial measurement unit (IMU). A weight associated with each of a plurality of filters is iteratively determined in an adaptive estimation model based on a match between position data and velocity data for each of the plurality of the filters conditioned by filter heading data for each of the plurality of the filters and the ongoing obtained position data and the velocity data of the object.

Abstract: A system and method for integrated data registration includes at least one host system and a first sensor where the first sensor provides a first input data. The system and method may further include a second sensor where the second sensor provides a second input data, a first navigation data source where the first navigation data source provides a third input data and a second navigation data source where the second navigation data source provides a fourth input data. The system and method may further include at least one non-transitory computer readable storage medium, in operative communication with the host system, first sensor, the second sensor, the first navigation source and the second navigation source, having at least one set of instructions encoded thereon that, when executed by at least one processor, performs operations to perform integrated data registration.

Abstract: A device for estimating an aircraft's speed relative to the ground and heading, while making no use of the rotation of the Earth or of the Earth's magnetic field. The device comprises in particular a first linear estimator that hybridizes a measurement of the speed of the aircraft relative to the ground as provided by a global navigation satellite system (GNSS) receiver with measurements of the acceleration and the attitudes of the aircraft coming from an attitude and heading reference system (AHRS) device without a gyrocompass and without a magnetometer. The first estimator is made linear by replacing the single “heading error estimate ??” state of prior art embodiments with two states, namely estimates of the sine and of the cosine of the heading error.

Abstract: The invention relates to a method for aligning an inertial navigation system borne by a static or quasi-static carrier, wherein: a plurality of alignment processes that are dimensioned for a plurality of amplitudes of movements of the carrier are implemented simultaneously with different alignment observation durations; a minimum observation duration that corresponds to the alignment observation duration for which the consistency of the alignment information obtained by means of alignment processes dimensioned for a given movement amplitude of the carrier is determined; and the alignment information is determined depending on alignment information determined for this minimum observation duration. The invention also relates to an associated inertial navigation system.

Abstract: The present invention provides a calculation method for visual navigation integrity monitoring. With the method, by use of an appropriate visual positioning model, a mathematical algorithm and rich navigation measurements, the positioning accuracy and availability of positioning results are improved, and the problem of insufficient performance of satellite integrity algorithms caused by impossible guarantee of availability of a GNSS in complex environments is solved, which is helpful to realize aircraft accurate approach and automatic landing and of great significance to ensure the safety of aviation flight.

Abstract: An iterative method determines a bias of a sensor for measuring a substantially continuous physical vector field in a reference frame, in which the sensor is linked in movement to a frame that is mobile in the reference frame. An iteration of the method includes: estimating a bias value in the mobile frame, correcting a measurement from the sensor of the estimated bias value, in the mobile frame, transforming the corrected measurement of the mobile frame in the reference frame, from a rotational change of frame operator between the mobile frame and the reference frame, and forming a criterion representative of a variation of the transformed corrected measurement.

Abstract: A method for tracking the navigation of a mobile carrier, in which an extended Kalman filter estimates, over successive iterations, a navigation state of the carrier. Each iteration propagates a previous navigation state of the carrier into a propagated state, updates the propagated state according to measurements acquired by at least one navigation sensor. The updating includes: calculating a linear correction term from an innovation representative of a difference between the measurements acquired by the navigation sensor and the propagated state, calculating an exponential of the linear correction in terms of a Lie group, calculating a first correction term expressed in a reference frame that is fixed relative to the carrier, calculating a second correction term expressed in an inertial reference frame in which the carrier is mobile, and adding the second correction term to the value of the variable contained in the propagated state.

Abstract: A system may include first and second sensors configured to be coupled to a vehicle and generate surface sensor signals representative of a surface on which a location marker is disposed, and generate marker sensor signals representative of the location marker. The system may also include a sensor processor configured to estimate at least one of a position or an orientation of the first sensor relative to the surface on which the location marker is disposed based at least in part on the surface sensor signals, and estimate at least one of a position or an orientation of the second sensor relative to the location marker based at least in part on the marker sensor signals. The sensor processor may be configured to calculate at least one of the position or the orientation of the vehicle relative to the location marker based at least in part on the estimations.

Abstract: A method, apparatus and computer-readable medium for landing a flight device are provided. The method includes: detecting whether the flight device meets a condition for landing; detecting whether a current landing area for the flight device is a safe landing area, when the flight device meets the condition for landing, wherein the safe landing area is an area on the ground which enables the flight device to land safely; and adjusting the current landing area for the flight device to the safe landing area, when the current landing area is not the safe landing area.

Abstract: Technologies for determining a user's location by a mobile computing device include detecting, based on sensed inertial characteristics of the mobile computing device, that a user of the mobile computing device has taken a physical step in a direction. The mobile computing device determines a directional heading of the mobile computing device in the direction and a variation of an orientation of the mobile computing device relative to a previous orientation of the mobile computing device at a previous physical step of the user based on the sensed inertial characteristics. The mobile computing device further applies a Kalman filter to determine a heading of the user based on the determined directional heading of the mobile computing device and the variation of the orientation and determines an estimated location of the user based on the user's determined heading, an estimated step length of the user, and a previous location of the user at the previous physical step.

Abstract: A navigation system to transition from a stationary alignment filter to an in-motion alignment filter is provided. The system comprises a processing unit configured to implement a stationary alignment Kalman filter (SAKF) in gyrocompass alignment mode to generate state estimates and provide corrections when the object is stationary, and to implement an algorithm to compute a covariance for the SAKF that accounts for uncertainty in the SAKF estimates; wherein the processing unit is further configured to implement a continuous alignment filter (CAF) that generates a secondary solution which remains unaffected by the SAKF corrections during a delay period accommodating a delay between the time of actual motion to the time of detected motion, and to implement an algorithm to compute a covariance for CAF that accounts for the uncertainty in CAF during delay period; and wherein outputs of the CAF and its covariance are communicated to an in-motion alignment filter.

Abstract: The invention relates to an antenna attitude measurement sensor as well as an attitude measurement method based on this sensor, wherein the antenna attitude measurement sensor is composed of a solar position sensor, a three axial gravity acceleration sensor, a GPS module, a CPU, a power supply module and a memory output module. Antenna attitude measurement method includes the following steps: A. installing antenna attitude measurement sensor; B. acquiring antenna geographic location, antenna hanging height, antenna pitch angle ? and rolling angle ? as well as the incident sunlight azimuth angle ? related to the solar position sensor and the corresponding standard time to form the azimuth angle; C. calculating the vertical incident angle ? and level incident angle ?; D calculating the antenna azimuth ?; E. memory output.

Abstract: Technologies for determining a user's location by a mobile computing device include detecting, based on sensed inertial characteristics of the mobile computing device, that a user of the mobile computing device has taken a physical step in a direction. The mobile computing device determines a directional heading of the mobile computing device in the direction and a variation of an orientation of the mobile computing device relative to a previous orientation of the mobile computing device at a previous physical step of the user based on the sensed inertial characteristics. The mobile computing device further applies a Kalman filter to determine a heading of the user based on the determined directional heading of the mobile computing device and the variation of the orientation and determines an estimated location of the user based on the user's determined heading, an estimated step length of the user, and a previous location of the user at the previous physical step.

Abstract: An avionics system comprises one or more attitude sources, each configured to produce a respective calculated attitude solution; at least one magnetometer configured to measure magnetic field; and at least one attitude monitor configured to use the respective calculated attitude solution from one of the attitude sources to project the measured magnetic field estimate or an Earth Magnetic Field Model (EMFM) estimate such that the measured magnetic field estimate and the EMFM estimate are in a common shared frame. The at least one attitude monitor is further configured to determine a difference between the measured magnetic field estimate and the EMFM estimate in the common shared frame. The at least one attitude monitor is further configured to output an alert, which indicates that the respective calculated attitude solution used to project the measured magnetic field estimate or the EMFM estimate is in error, if the difference exceeds a predetermined threshold.

Abstract: A method for evaluating output signals of a rotational rate sensor unit, including providing an n-tuple of angular speed values measured by at least one rotational rate sensor of the rotational rate sensor unit, in a first step; determining an intermediate value as a function of the n-tuple of angular speed values, in a second step; calculating a new change of orientation value as a function of the intermediate value and an earlier change of orientation value stored in a register of the rotational rate sensor unit, in a third step; and storing the new change of orientation value in the register, in a fourth step, repeating the first, second, third, and fourth step until, the new change of orientation value is read out by an external data processing unit connected to the rotational rate sensor unit, and/or, an exceeding of a threshold value is detected.

Abstract: Embodiments are directed towards multi-level entity classification. An object associated with an entity is received. In one embodiment the object comprises and email and the entity comprises the IP address of a sending email server. If the entity has already been classified, as indicated by an entity classification cache, then a corresponding action is taken on the object. However, if the entity has not been classified, the entity is submitted to a fast classifier for classification. A feature collector concurrently fetches available features, including fast features and full features. The fast classifier classifies the entity based on the fast features, storing the result in the entity classification cache. Subsequent objects associated with the entity are processed based on the cached result of the fast classifier. Then, a full classifier classifies the entity based on at least the full features, storing the result in the entity classification cache.

Abstract: The present disclosure is directed toward systems and methods for enabling autonomous landing of an unmanned aerial vehicle. For example, systems and methods described herein enable autonomous landing of the unmanned aerial vehicle by providing an unmanned aerial vehicle ground station with various guidance systems for guiding the autonomous landing. In some embodiments, the guidance systems enable autonomous landing by providing one or more LEDs. In other embodiments, the guidance systems enable autonomous landing by providing various types of transmitted energy waves. In at least one embodiment, the guidance systems enable autonomous landing by providing a two-stage landing system that includes two or more types of transmitted energy.

Abstract: According to one aspect, a method of determining an attitude matrix on a portable electronic device. The method includes determining a first attitude matrix gradient using data from at least one of an accelerometer and a magnetometer, determining a second attitude matrix gradient using data from a gyroscope, fusing the first attitude matrix gradient and the second attitude matrix gradient based on a mixing coefficient to generate a fused gradient, and based on the fused gradient, updating a fine attitude matrix for the portable electronic device.

Abstract: Methods, systems, and computer readable storage media are presented for directional scaling of inertial path data to satisfy ranging constraints. The presented techniques take into account scaling confidence information. In addition to bounding potential scale corrections based on the reliability of the inertial path and the magnetic heading confidence, the techniques bound potential scale parameters based on constraints and solve for directional scale parameters.

Abstract: Systems and methods for navigation using cross correlation on evidence grids are provided. In one embodiment, a system for using cross-correlated evidence grids to acquire navigation information comprises: a navigation processor coupled to an inertial measurement unit, the navigation processor configured to generate a navigation solution; a sensor configured to scan an environment; an evidence grid creator coupled to the sensor and the navigation processor, wherein the evidence grid creator is configured to generate a current evidence grid based on data received from the sensor and the navigation solution; a correlator configured to correlate the current evidence grid against a historical evidence grid stored in a memory to produce displacement information; and where the navigation processor receives correction data derived from correlation of evidence grids and adjusts the navigation solution based on the correction data.

Abstract: It is presumed and commonly accepted by those skilled in the art of satellite navigation and Kalman filter design that the filter must be provided with the tracker position and velocity a priori in order to determine target position and velocity. Indeed, it is generally asserted that without a priori knowledge (known or measured values) of the tracker position and velocity, line of sight measurements between satellites do not contain adequate information to infer target states. Passive and autonomous navigation of space vehicles without a priori values for the position and velocity of either the target or tracker vehicle is achieved by reconfiguring the extended Kalman filter, or more generally any predictor/correction class filter, to include states for both the target and tracker vehicles. The target and tracker vehicles must both follow trajectories in an inertial frame of reference through the gravitational field of a gravitational body having a known gravitational model.

Abstract: Embodiments of the present invention provide improved systems and methods for estimating N-dimensional parameters while sensing fewer than N dimensions. In one embodiment a navigational system comprises a processor and an inertial measurement unit (IMU) that provides an output to the processor, the processor providing a navigation solution based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional parameter. Further, the navigational system includes at most two sensors that provide an output to the processor, wherein the processor computes an estimate of an n-dimensional parameter from the output of the at most two sensors for bounding errors in the n-dimensional parameter as calculated by the processor when the trajectory measured by the IMU satisfies movement requirements, wherein “n” is greater than the number of the at most two sensors.

Abstract: A system and method for estimating the position of an object, such as a person, animal, or machine. The system includes first and second inertial measurement units, a first and second originator antennas, and a first and second transponder antennas. The system uses data from the inertial measurement units to estimate a position of the object. The system also calculates a range measurement between the first originator antenna and first transponder antenna. The system calculates a first CPD measurement between the second transponder antenna and the first originator antenna, and a second CPD measurement between the second originator antenna and the first transponder antenna. The range measurement and at least one CPD measurement are used to update a Kalman filter for estimating the position of the object. The system determines also updates the Kalman filter when one of the inertial measurement units is in a zero-velocity condition.

Abstract: A positioning device includes a map data storing unit configured to store map data; autonomous sensors configured to detect behavior information of a moving object; an inertial positioning unit configured to detect an estimated position of the moving object by applying the behavior information detected by the autonomous sensors to positioning results obtained by an electronic navigation positioning unit such as a GPS; a planimetric feature detecting unit configured to detect a planimetric feature located around a road; a planimetric feature position identifying unit configured to identify a position of the planimetric feature; a planimetric feature reference positioning unit configured to estimate a planimetric feature estimated position of the moving object by using the position of the planimetric feature as a reference; and a position estimating unit configured to estimate a position of the moving object by applying the estimated position and the planimetric feature estimated position to a Kalman filter.

Abstract: A navigation system includes at least one inertial sensor configured to detect motion of the system and generate inertial data; at least one aiding device configured to generate aiding device measurement data; at least one processing unit configured to generate an un-smoothed navigation solution inclusive of navigation state variable error resets based on the inertial data and the aiding device measurement data; wherein the at least one processing unit is further configured to sum the state variable error resets into a cumulative sum of the state variable error resets; wherein the at least one processing unit is further configured to high pass filter the cumulative sum of the state variable error resets; and wherein the at least one processing unit is further configured to subtract the high pass filtered cumulative sum of the state variable error resets from the un-smoothed navigation solution to generate a smoothed navigation solution.

Abstract: The invention relates to a guidance system comprising estimation means able to estimate, in the course of flight, the attitude and the aerodynamic speed of a projectile, as well as the variations in the speed of the wind, on the basis of guidance orders formulated by guidance means of the guidance system, of a reference trajectory and of measurements obtained by measurement means of the system, using a model of the dynamic behavior of the projectile and a model of the dynamics of the wind.

Abstract: In a GPS composite navigation apparatus of a configuration having a GPS receiver, variation in an estimated position, an estimated velocity, and an estimated azimuth of a moving body when the moving body is not moving is resolved, and the GPS/INS integrated navigation system with good response characteristics from a stationary state to a moving state. A stationary detector for determining the stationary state of the moving body is provided, and when it is determined to be the stationary state by the stationary detector, a measurement model used for measurement-update of a Kalman filter is changed, while a changed amount of an error covariance matrix by the update is corrected.

Abstract: A state is added to a Kalman filter to model GPS multipath errors. The multipath states may be modeled as either a random walk model or a Gauss-Markov process. The choice of the model depends on the characteristics of the multi-path error and the GPS receiver. Adding this state to the Kalman filter to model multipath improves the navigation system's robustness when operating as a deeply integrated system when multipath is present.

Abstract: A position calculation method and apparatus are described. The position calculation apparatus may include an inertial measurement unit and be configured to be coupled with at least one sensor unit for detecting a physical event for use in position calculation. The presence of and type sensor unit may identified, and the position processing to be undertaken may depend on this identification.

Abstract: The present disclosure provides systems and methods that improve the pointing accuracy of a spacecraft using temperature-sensitive gyros (e.g., MEMS gyros) by using a temperature bias model to compensate for temperature biases of the gyros and using attitude data (e.g., star tracker data) to automatically and continuously calibrate the temperature bias model over the life of the spacecraft. When star tracker data is unavailable (e.g., due to sun interference), the most recently updated temperature bias model is used in open-loop to provide improved estimation of the gyro biases and improved attitude estimation.

Abstract: Embodiments include systems and methods of navigation. In on embodiment, a plurality of position and motion states of a vehicle are estimated. The states may be estimated based on information received from a satellite receiver and an inertial measurement sensor. Estimating the states comprises performing one or more of a plurality of update steps at the rate that information is received from the satellite receiver. The states are estimated at a rate greater than the rate at which the update steps are performed. In one embodiment, the states are estimated using a stepped extended Kalman filter.

Abstract: Systems and methods to incorporate master navigation system resets during transfer alignment are provided. In one embodiment, a system comprises: a set of local inertial sensors; a local navigation processor coupled to local inertial sensors, the local navigation processor receiving inertial navigation data from local inertial sensors and converting the data into a navigation solution; a local Kalman filter (LKF) coupled to the local navigation processor and a master Kalman filter (MKF), the LKF receiving the navigation solution. The LKF receives from the MKF a Precision Transfer Alignment Message (PTAM) that includes at least one navigation aid measurement. The LKF inputs the navigation aid measurement into a measurement formation algorithm and calculates a measurement residual. The LKF receives from the MKF a Reset Transfer Alignment Message (RTAM) that includes a bias correction. The LKF inputs the bias correction into a state propagation algorithm to add to a navigation state.

Abstract: Systems and methods to incorporate master navigation system resets during transfer alignment are provided. In one embodiment, a system comprises: a set of local inertial sensors; a local navigation processor coupled to local inertial sensors, the local navigation processor receiving inertial navigation data from local inertial sensors and converting the data into a navigation solution; a local Kalman filter (LKF) coupled to the local navigation processor and a master Kalman filter (MKF), the LKF receiving the navigation solution. The LKF receives from the MKF a Precision Transfer Alignment Message (PTAM) that includes at least one navigation aid measurement. The LKF inputs the navigation aid measurement into a measurement formation algorithm and calculates a measurement residual. The LKF receives from the MKF a Reset Transfer Alignment Message (RTAM) that includes a bias correction. The LKF inputs the bias correction into a state propagation algorithm to add to a navigation state.

Abstract: A computerized system and method for peak-seeking-control that uses a unique Kalman filter design to optimize a control loop, in real time, to either maximize or minimize a performance function of a physical object (“plant”). The system and method achieves more accurate and efficient peak-seeking-control by using a time-varying Kalman filter to estimate both the performance function gradient (slope) and Hessian (curvature) based on direct position measurements of the plant, and does not rely upon modeling the plant response to persistent excitation. The system and method can be naturally applied in various applications in which plant performance functions have multiple independent parameters, and it does not depend upon frequency separation to distinguish between system dimensions.

Abstract: Inertial navigation systems for wheeled vehicles with constrained motion degrees of freedom are described.

Abstract: Systems and methods for determining a position of a vehicle are described. The system includes at least one GNSS sensor mounted to the vehicle for receiving GNSS signals of a global positioning system and at least one physical sensor mounted to the vehicle for generating physical data indicative of a physical parameter of at least a part of the vehicle. The system also includes a recursive statistical estimator, such as a Kalman Filter, in communication with the GNSS sensor(s) for seeding the recursive statistical estimator with an output of the GNSS sensor(s) to determine an estimated position of the vehicle. A data fusion module combines the estimated position and velocity of the vehicle with the physical data thus generating combined data, which is used to seed the recursive statistical estimator to determine an updated estimated position of the vehicle.

Abstract: A system for navigation and tracking may include an inertial navigation system adapted to generate a replica GNSS signal and a global navigation satellite system. The global navigation satellite system may include a module to digitize a GNSS signal received from a constellation of global navigation satellites. A correlator receives the digitized GNSS signal and the replica GNSS signal. The correlator correlates the digitized GNSS signal to the replica GNSS signal to generate a correlated GNSS signal. A coherent integration module coherently integrates the correlated GNSS signal to generate an integrated signal having a predetermined rate. A filter receives the integrated signal and generates a data signal for navigation and tracking. An output device may present the navigation and tracking information based on the data signal, or the navigation and tracking information may be used to provide guidance for a vehicle or may be used to track a target.

Abstract: A system comprises at least one inertial sensor operable to provide inertial sensor data during a trip; a processing unit coupled to the at least one inertial sensor, the processing unit operable to calculate navigation data based on the inertial sensor data and to estimate error in the inertial sensor data, wherein the processing unit is further operable to adjust subsequent inertial sensor data received during the trip from the at least one inertial sensor in order to compensate for the estimated error; and a memory coupled to the navigation unit and operable to store data between power cycles; wherein the processing unit is further operable to calculate a current trip error estimate from a plurality of error estimates during the trip and to estimate a repeatability error component based on the current trip error estimate and previous trip error estimates stored in the memory; wherein the repeatability error component is stored in the memory, the processing unit being further operable to update inertial sen

Abstract: Embodiments of the present invention provide improved systems and methods for estimating N-dimensional parameters while sensing fewer than N dimensions. In one embodiment a navigational system comprises a processor and an inertial measurement unit (IMU) that provides an output to the processor, the processor providing a navigation solution based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional parameter. Further, the navigational system includes at most two sensors that provide an output to the processor, wherein the processor computes an estimate of an n-dimensional parameter from the output of the at most two sensors for bounding errors in the n-dimensional parameter as calculated by the processor when the trajectory measured by the IMU satisfies movement requirements, wherein “n” is greater than the number of the at most two sensors.

Abstract: A method for processing data in an inertial navigation system having a Kalman filter and computer-readable storage medium containing instructions to configure a processor to perform the same. The method produces more accurate estimates of the position, velocity and attitude of the inertial measurement unit. The method is fully automatic and enables zero-velocity updates and fixed-azimuth updates to be performed simultaneously. The method may also include a multi-stage filtering process to filter digital compass data when used in an environment with extraterrestrial magnetic field sources. The method may also include a fixed-lag smoother to improve estimates of the position, velocity and attitude of the inertial measurement unit. The method also may include processes to constrain altitude errors.

Abstract: Systems and methods for navigation using cross correlation on evidence grids are provided. In one embodiment, a system for using cross-correlated evidence grids to acquire navigation information comprises: a navigation processor coupled to an inertial measurement unit, the navigation processor configured to generate a navigation solution; a sensor configured to scan an environment; an evidence grid creator coupled to the sensor and the navigation processor, wherein the evidence grid creator is configured to generate a current evidence grid based on data received from the sensor and the navigation solution; a correlator configured to correlate the current evidence grid against a historical evidence grid stored in a memory to produce displacement information; and where the navigation processor receives correction data derived from correlation of evidence grids and adjusts the navigation solution based on the correction data.

Abstract: An inertial system is provided. The system includes at least one inertial sensor, a processing unit and a plurality of Kalman filters implemented in the processing unit. The Kalman filters receive information from the at least one inertial sensor. At most one of the plurality of Kalman filters has processed zero velocity updates on the last cycle.

Abstract: Systems and methods are provided for tracking a moving person. The system comprises a controller configured to receive acceleration data that characterizes an acceleration of the moving person in three dimensions. The controller comprises a step rate component that determines a step rate for the person based on a vertical component of the acceleration data. The controller also comprises a body offset component that determines a body offset angle based on a spectral analysis of the acceleration data and the step rate. The controller further comprises a velocity component that determines a reference velocity vector based on the body offset angle and the step rate.

Abstract: Inertial navigation systems for wheeled vehicles with constrained motion degrees of freedom are described.