Abstract: Methods and systems to process and assure integrity of radar measurements, detect the effects of GNSS jamming and/or spoofing events, identify GNSS measurements affected by the GNSS jamming and/or spoofing events, and assure the integrity of the GNSS measurements unaffected by jamming and/or spoofing events in a vehicle navigation system are disclosed. The methods are implemented to integrate inertial measurements, GNSS measurements, and radar measurements for the vehicle, and apply solution separation techniques to all of the measurements. The solution separation techniques use a main filter for hybridization of the inertial measurements, the GNSS measurements, and the radar measurements, with additional sub-solution filters and sub-sub-solution filters that use combinations of these measurements. This provides common processing of the GNSS and radar sensors in a single hybridization and solution separation framework.

Abstract: A method of integrity monitoring for visual odometry comprises capturing a first image at a first time epoch with stereo vision sensors, capturing a second image at a second time epoch, and extracting features from the images. A temporal feature matching process is performed to match the extracted features, using a feature mismatching limiting discriminator. A range, or depth, recovery process is performed to provide stereo feature matching between two images taken by the stereo vision sensors at the same time epoch, using a range error limiting discriminator. An outlier rejection process is performed using a modified RANSAC technique to limit feature moving events. Feature error magnitude and fault probabilities are characterized using overbounding Gaussian models.

Abstract: Systems and methods are described that illustrate how to determine whether an image includes a travel way, and if so how to determine an angle between a longitudinal axis of a vehicle and a longitudinal axis of a travel way line, and a shortest distance between a reference point on a vehicle and a longitudinal axis of the travel way line.

Abstract: Methods and systems to process and assure integrity of DME and/or VOR measurements, detect the effects of GNSS jamming and/or spoofing events, identify GNSS measurements affected by the GNSS jamming and/or spoofing events, and assure the integrity of the GNSS measurements unaffected by jamming and/or spoofing events in a vehicle navigation system are disclosed. The methods are implemented to integrate inertial measurements, GNSS measurements, and DME/VOR measurements for the vehicle, and apply solution separation techniques to all of the measurements. The solution separation techniques use a main filter for hybridization of the inertial measurements, the GNSS measurements, and the DME/VOR measurements, with additional sub-solution filters and sub-sub-solution filters that use combinations of these measurements. This provides common processing of the GNSS and DME/VOR sensors in a single hybridization and solution separation framework.

Abstract: A system to provide navigation solutions for vehicle landing guidance comprises onboard aiding sensors, an IMU, a radar altimeter, a map database, and a navigation system including a navigation filter that outputs estimated kinematic state statistics for the vehicle. An onboard processor inputs horizontal and vertical position statistics from the navigation filter into the map database, and computes an estimated ground/object height, ground/object velocity, ground/object acceleration, and error statistics thereof, based on terrain and object map data.

Abstract: A system for integrity monitoring comprises a processor onboard a vehicle, a terrain map database, vision sensors, and inertial sensors. Each vision sensor has an overlapping FOV with at least one other vision sensor. The processor performs integrity monitoring of kinematic states of the vehicle, and comprises a plurality of first level filter sets, each including multiple position PDF filters. A consistency monitor is coupled to each first level filter set. Second level filter sets, each including multiple position PDF filters and a navigation filter, are coupled to the consistency monitor, the map database, the vision sensors, and the inertial sensors. Consistency check modules are each coupled to a respective second level filter set. A third level fusion filter is coupled to each of the consistency check modules. An integrity monitor is coupled to the fusion filter and assures integrity of a final estimate of the vehicle kinematic state statistics.

Abstract: A method of determining three-dimensional attitude is provided. The method includes measuring a carrier phase of each satellite signal received at plurality of spaced antenna. A carrier phase difference between the measured carrier phase for each satellite signal from each satellite received at each antenna is determined. The integrity of the integer ambiguity resolution relating to the carrier phase difference is assured by applying a least-square-error solution using differential carrier phase measurements with applied integer ambiguities between at least two of the plurality of antennas and observing measurement residuals after the least-square-error solution is computed and applying an instantaneous test, an interval test and a solution separation function. Three-dimensional attitude is determined from the carrier phase differences upon completion of the integer ambiguity resolution and the assurance of integrity of the integer ambiguity resolution.

Abstract: In one embodiment, a vision aided navigation system comprises: at least one image sensor configured to produce image frames of a surrounding environment; a feature extractor configured to extract at least one image feature from a first image frame; a navigation filter configured to output a navigation solution based navigation data from a navigation device and changes in position of the image feature in the images; a feature tracker to receive the image frames and predict a location of the image feature in a subsequent image frame; a dynamic localized parameter adjuster to adjust at least one image parameter of the subsequent image frame; and wherein the feature tracker is configured so that when the image feature cannot be identified in the subsequent image frame within a bounded region around the predicted location, the dynamic localized parameter adjuster adjusts the at least one image parameter within the bounded region.

Abstract: A system to provide navigation solutions for vehicle landing guidance comprises onboard aiding sensors, an IMU, a radar altimeter, a map database, and a navigation system including a navigation filter that outputs estimated kinematic state statistics for the vehicle. An onboard processor inputs horizontal and vertical position statistics from the navigation filter into the map database, and computes an estimated ground/object height, ground/object velocity, ground/object acceleration, and error statistics thereof, based on terrain and object map data.

Abstract: A ground map monitor method comprises obtaining positions of communication nodes in a communications network, selecting transmission and reception nodes from the communication nodes, and measuring bistatic signals between the transmission and reception nodes to determine nominal signal performance characteristics for the bistatic signals, including reflected signal time delays, frequency shifts, and power levels. The method further comprises monitoring the bistatic signals for changes to nominal signal performance characteristics. The method uses discriminators between the nominal signal performance characteristics and a current performance level of the bistatic signals, and compares the discriminators against performance thresholds, to determine whether current signal performance characteristics have varied from their nominal levels.

Abstract: In one embodiment, a vision aided navigation system comprises: at least one image sensor configured to produce image frames of a surrounding environment; a feature extractor configured to extract at least one image feature from a first image frame; a navigation filter configured to output a navigation solution based navigation data from a navigation device and changes in position of the image feature in the images; a feature tracker to receive the image frames and predict a location of the image feature in a subsequent image frame; a dynamic localized parameter adjuster to adjust at least one image parameter of the subsequent image frame; and wherein the feature tracker is configured so that when the image feature cannot be identified in the subsequent image frame within a bounded region around the predicted location, the dynamic localized parameter adjuster adjusts the at least one image parameter within the bounded region.

Abstract: Systems and methods for integrity monitoring of odometry measurements within a navigation system are provided herein. In certain embodiments, a system includes imaging sensors that generate image frames from optical inputs. The system also includes a GNSS receiver that provides pseudorange measurements; and computational devices that receive the image frames and the pseudorange measurements. Further, the computational devices compute odometry information from image frames acquired at different times; and calculate a full solution for the system based on the pseudorange measurements and the odometry information. Additionally, the computational devices calculate sub-solutions for the system based on subsets of the pseudorange measurements and the odometry information, wherein one of the sub-solutions is not based on the odometry information.

Abstract: A navigation system for a vehicle comprises onboard sensors including a vision sensor, and an onboard map database of terrain maps. An onboard processer, coupled to the sensors and map database, includes a position PDF filter, which performs a method comprising: receiving image data from the vision sensor corresponding to terrain images captured by the vision sensor of a given area; receiving map data from the map database corresponding to a terrain map of the area; generating a first PDF of image features in the image data; generating a second PDF of map features in the map data; generating a measurement vector PDF by a convolution of the first PDF and second PDF; estimating a position vector PDF using a non-linear filter that receives the measurement vector PDF; and generating statistics from the estimated position vector PDF that include real-time measurement errors of position and angular orientation of the vehicle.

Abstract: A method of integrity monitoring for visual odometry comprises capturing a first image at a first time epoch with stereo vision sensors, capturing a second image at a second time epoch, and extracting features from the images. A temporal feature matching process is performed to match the extracted features, using a feature mismatching limiting discriminator. A range, or depth, recovery process is performed to provide stereo feature matching between two images taken by the stereo vision sensors at the same time epoch, using a range error limiting discriminator. An outlier rejection process is performed using a modified RANSAC technique to limit feature moving events. Feature error magnitude and fault probabilities are characterized using overbounding Gaussian models.

Abstract: A method of assuring integrity of range measurements and position solutions comprises obtaining range measurement statistics between network nodes, performing a snapshot integrity test for the range measurement statistics, and performing a sequential integrity test using the range measurement statistics. The snapshot integrity test comprises using Gram matrices with a current configuration of the nodes; performing a singular value consistency check using the Gram matrices against a user selected threshold; and detecting and excluding range measurement statistics with instantaneous errors that cause the singular value to exceed the threshold.

Abstract: A system for integrity monitoring comprises a processor onboard a vehicle, a terrain map database, vision sensors, and inertial sensors. Each vision sensor has an overlapping FOV with at least one other vision sensor. The processor performs integrity monitoring of kinematic states of the vehicle, and comprises a plurality of first level filter sets, each including multiple position PDF filters. A consistency monitor is coupled to each first level filter set. Second level filter sets, each including multiple position PDF filters and a navigation filter, are coupled to the consistency monitor, the map database, the vision sensors, and the inertial sensors. Consistency check modules are each coupled to a respective second level filter set. A third level fusion filter is coupled to each of the consistency check modules. An integrity monitor is coupled to the fusion filter and assures integrity of a final estimate of the vehicle kinematic state statistics.

Abstract: A multiple faulty global navigation satellite signal detecting system is provided. The system includes at least one pair of spaced antennas, at least one aiding source and processor. The at least one pair of spaced antennas are configured to receive satellite signals from a plurality of satellites. The at least one aiding source is used to generate aiding source position estimate signals. The processor is in communication with each antenna and the at least one aiding source. The processor is configured to determine signals blocks. The signal blocks being a collection of subsets of the determined difference signals and a covariance matrix for the difference signals. The processor further configured to generate a union of good signals from all the good blocks and a complementary set of bad signals.

Abstract: A method for planning a vehicle trajectory is provided. The method comprises obtaining an edge map representation corresponding to one or more terrain images of a given area, and identifying a total number of edge pixels in each of a plurality of sub-regions of the edge map representation. The method further comprises determining a measurement probability density function (PDF) for each of the sub-regions based on the number of edge pixels with information content in each sub-region. The method then computes a trajectory cost for each of the sub-regions by dividing a user-selected scalar by a sum of: a user-selected value and the number of edge pixels with information content in each sub-region. Thereafter, the method selects a trajectory for navigation of a vehicle over the given area based on the trajectory cost for each of the sub-regions.

Abstract: A navigation system for a vehicle comprises onboard sensors including a vision sensor, and an onboard map database of terrain maps. An onboard processer, coupled to the sensors and map database, includes a position PDF filter, which performs a method comprising: receiving image data from the vision sensor corresponding to terrain images captured by the vision sensor of a given area; receiving map data from the map database corresponding to a terrain map of the area; generating a first PDF of image features in the image data; generating a second PDF of map features in the map data; generating a measurement vector PDF by a convolution of the first PDF and second PDF; estimating a position vector PDF using a non-linear filter that receives the measurement vector PDF; and generating statistics from the estimated position vector PDF that include real-time measurement errors of position and angular orientation of the vehicle.

Abstract: Systems and methods are described that illustrate how to determine whether an image includes a travel way, and if so how to determine an angle between a longitudinal axis of a vehicle and a longitudinal axis of a travel way line, and a shortest distance between a reference point on a vehicle and a longitudinal axis of the travel way line.