Patent Description:
For vehicles operating in urban environments, especially airborne vehicles, even a momentary false determination of position or loss of primary position information can lead to a collision with structures within the urban environment. Thus, vehicles traversing urban environments require uninterrupted, accurate position data to operate in an urban environment.

While the aforementioned problem can occur when a human operates a vehicle, the problem is can be more acute for an autonomous vehicle. In some cases, autonomous vehicles lack secondary systems (in addition to a GNSS receiver) for determining their position. Moreover, some autonomous vehicles cannot determine when their GNSS receiver generates inaccurate position data, e.g. due to multipath of satellite signals arising from obstacles such as buildings. When an autonomous vehicle cannot determine its location, the vehicle will not be able to properly land and may run out of power attempting to determine its position.

One often used secondary system for position determination is an inertial measurement unit (IMU). An IMU determines location based upon measuring linear accelerations and rotation rates. IMUs having high precision are cost prohibitive for low cost autonomous vehicles. Therefore, there is a need for a low cost and reliable alternate for determining vehicle position.

<CIT> describes a method and system for terrain aided navigation using on-vehicle sensing elements.

The invention is defined in the attached independent claims to which reference should now be made. Further, optional features may be found in the subclaims appended thereto.

A method is provided as defined in the appended claim <NUM>. The method comprises among others: : projecting at least one directional beam from at least one phased array radar, where a radar signal is emitted and a radar return signal may be received in each directional beam; generating at least one radar return image from at least one radar return signal; correlating the radar return image with a three-dimensional map database; and determining at least one of a three-dimensional position and a velocity of a vehicle based upon the correlation.

Understanding that the drawings depict only some embodiments and are not therefore to be considered limiting in scope, the exemplary embodiments will be described with additional specificity and detail using the accompanying drawings, in which:.

In accordance with common practice, the various described features are not drawn to scale but are drawn to emphasize specific features relevant to the exemplary embodiments.

In the following detailed description, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific and landing vehicle, such as an airborne drone; however, the vehicle <NUM> may be any other type of vehicle including without limitation a spaceborne or terrestrial vehicle. Such other types of vehicles may be non-airborne vehicles (including drones). The vehicle <NUM> includes at least one radar, e.g. a forward-facing radar.

For pedagogical purposes, two radars will be illustrated: a forward-facing radar <NUM> and a downward-facing radar <NUM>. The forward-facing radar <NUM> generates information, e.g. about obstacles such as structures, in front of the vehicle <NUM>. The downward-facing radar <NUM> generates information, e.g. about obstacles such as structures, below the vehicle <NUM>. Such information can be used by the vehicle <NUM> to avoid collisions with obstacles <NUM>, e.g. in an urban environment.

Obstacles <NUM> include stationary obstacles (e.g. structures such as building(s) and tree(s)) and moving obstacles (e.g. other vehicle(s)). Optionally, the vehicle <NUM> can travel autonomously under control of the navigation system <NUM>. With knowledge of the location of these obstacles <NUM>, the navigation system can re-route the vehicle <NUM> to avoid collision with the obstacles <NUM>.

However, in some examples one or more radars can be employed in the vehicle <NUM> facing directions other than forward- or downward-facing. The one or more radars may be collectively referred to as "radars". Multiple radars may be used to increase the field of regard, e.g. up to <NUM>°. Such radars can be mounted on and/or in the vehicle <NUM>. Description of the forward-facing radar <NUM> and the downward-facing radar <NUM> applies to all radars employed in the vehicle <NUM>.

The forward-facing radar <NUM> and the downward-facing radar <NUM> are configured to emit radar signals and to receive return radar signals. The radar signals reflect off objects in the environment. The reflectivity of an object depends on many factors including the shape of the object, the material of the object, and the proximity of different materials. The reflected return radar signals from the radars <NUM>, <NUM> can be used to determine the three-dimensional position of objects within a field of regard of a radar based upon the intensity of the return radar signal, beam direction, and the delay of return signals with the corresponding radar signals. Some aspects of an obstacle <NUM>, such as a corner of a building, will be more readily identifiable than other aspects, such as a flat window pane. Thus, certain features of objects within an urban environment will be more identifiable than others.

In the example shown in <FIG>, the forward-facing radar <NUM> is mounted on, e.g. the front of, the vehicle <NUM> such that the forward-facing radar <NUM> provides a radar return image of a volume in front of the vehicle <NUM>. The forward-facing radar <NUM> is configured to emit radar signals in at least one directional beam. In some examples, forward-facing radar <NUM> is configured to emit at least one narrow beam radio signal and receive a corresponding reflected radio signal in each of the at least one narrow beams. For example, a downward directional beam <NUM> would be scanned, e.g. electronically, across a wide, e.g. a hemispherical volume, in front of the vehicle <NUM>. In a forward directional beam <NUM>, a forward radar signal 105a is transmitted, and a forward return signal 105b is received if the forward radar signal 105a is reflected from an obstacle <NUM> upon which the forward radar signal 105a impinges. In some examples, the forward-facing radar <NUM> is configured to emit and receive radio signals, in at least one beam. One or more beams are scanned, e.g. electronically, to image obstacles <NUM> within a volume in front of the vehicle <NUM>.

In the example shown in <FIG>, the downward-facing radar <NUM> is mounted on, e.g. the bottom of, the vehicle <NUM> such that the downward-facing radar <NUM> provides a radar return image of a volume below the vehicle <NUM>. The downward-facing radar <NUM> is configured to emit radar signals in at least one directional beam. In some examples, downward-facing radar <NUM> is configured to emit at least one narrow beam radio signal, and receive a corresponding reflected radio signal in each of the at least one narrow beams. For example, a downward directional beam <NUM> would be scanned, e.g. electronically, across a wide, e.g. a hemispherical volume, in front of the vehicle <NUM>. In the downward directional beam <NUM>, a downward radar signal 103a is transmitted, and a downward return signal 103b is received if the downward radar signal 103a is reflected from an obstacle <NUM> upon which the downward radar signal 103a impinges. In some examples, the downward-facing radar <NUM> is configured to emit and receive radio signals, in at least one beam. One or more beams are scanned, e.g. electronically, to image obstacles <NUM> within a volume below the vehicle <NUM>.

As a result, each radar generates a radar return image for an instant in time or a time period. Each radar return image identifies obstacles <NUM> in the image and the three-dimensional position of the reflective surfaces of each of such obstacles <NUM> relative to the vehicle <NUM>. For non-airborne vehicles, the downward-facing radar <NUM> may be absent or configured to face in another direction.

In some examples, each radar is a phased-array radar, a Synthetic Aperture Radar (SAR) or an Inverse SAR. A phased-array radar may be implemented as described in <CIT>, which is herein incorporated by reference in its entirety. A phased-array radar is suitable for vehicles because it can electronically scan a volume, and thus does not require heavy and bulky mechanical scanning hardware.

The phased-array radar described in the '<NUM> Patent includes multiple radar units, a clock, and a processing system. The radar signal transmitted by each radar units is phased locked to a clock. Each radar unit can subsequently adjust the phase and amplitude of its transmitted radar signal. By doing so, the phased-array radar can be tailored to emit one or more beams and scan the one or more beams.

SAR or ISAR system utilizes a single non-scanning radar on a vehicle and the motion of respectively the vehicle or target to produce a detailed image, e.g. of the urban environment. The resulting radar images provide a three-dimensional image of the radar returns through computation. In some examples, the SAR and ISAR radars process the radar return signals and provide the navigation system <NUM> with a radar return image. In other examples, the radar return signals described herein are provided to the navigation system <NUM> and the navigation system <NUM> is configured to process the radar return signals into a radar return image.

In one example, the forward-facing radar <NUM> and the downward-facing radar <NUM> are each implemented as scanning radar, e.g. phased-array radar. In such an example, the forward-facing radar <NUM> emits one or more beams which scan a region in front of the vehicle <NUM> to generate a forward radar return image derived from the forward return signal 105b; the downward-facing radar <NUM> emits one or more beams which scan a region below the vehicle <NUM> to generate a downward radar return image derived from the forward return signal 103b.

In the example shown in <FIG>, the navigation system <NUM> is configured to receive forward and downward radar return images from the forward-facing radar <NUM> and the downward-facing radar <NUM>. In some examples, the navigation system <NUM> is configured to include a three-dimensional map database. In some examples, the navigation system <NUM> is configured to receive information from other components of the navigation system <NUM> (e.g. a GNSS system, an altimeter, and/or an attitude and heading reference system (AHRS)). In the example shown in <FIG>, the navigation system <NUM> is configured to determine three-dimensional position and velocity of the vehicle <NUM>. Furthermore, the navigation system <NUM> is coupled to flight controls and actuators of the vehicle <NUM>.

In some embodiments, the radar return image(s), each of which may identify one or more obstacles <NUM>, are compared to a three-dimensional map database stored within the vehicle <NUM>; alternatively, the three-dimensional map database may be stored off the vehicle <NUM> (e.g. in a cloud computing system) and accessed remotely through a communications system <NUM> on the vehicle. Reflective features, e.g. corners, sharp angles, or certain materials, can be overlaid on a high-resolution ground map or image. Using image processing techniques, e.g. edge detection, the reflective features of radar return image(s) can be aligned with the three-dimensional map database, e.g. comprising a high-resolution ground map for example generated by photography or other imaging. The more reflective features, e.g. surfaces and/or edges, that can be used to align with the three-dimensional map, the more accurate vehicle three-dimensional position and/or, velocity can be determined.

In some embodiments, the radar return image(s) may be SAR or ISAR images. In other embodiments, the three-dimensional map may be an optical image.

In other embodiments, the three-dimensional map database comprises multiple views of a similar path. Reflective features, e.g. corners, sharp angles, or certain materials, can be overlaid on a high-resolution ground map or image. Using image processing techniques, e.g. edge detection, the reflective features of radar return image(s) can be aligned with one or more views of the three-dimensional map database. Once the radar return image(s) are correlated with data in the three-dimensional map database, algorithms are used to determine vehicle's three-dimensional position and/or velocity.

In other embodiments or in combination of the above embodiment, the three-dimensional map database comprises past radar return images collected by vehicle(s) flying similar routes. Each vehicle periodically, e.g. every second, captures radar return images during its travel over such routes and is aware of its location and attitude when doing so. Thus, each radar return image can be used to determine the distance of the obstacles (corresponding to radar return signals) from a vehicle, and the location of the obstacles (or surfaces thereof). These past radar return images can be used individually or in combination as templates in the three-dimensional map database that are then correlated with commonly used-image recognition pattern matching algorithms as the vehicle is flying. Once the radar return image is correlated to a past radar return image (or an amalgamation of past radar return images), angular offset information (e.g. based on vehicle attitude and/or radar beam angle) and radar distance information are used to determine three-dimensional position and velocity of the vehicle. In one embodiment, the position of the vehicle can be determined by determining the distance of the vehicle from one or more obstacles (or surfaces thereof), e.g. using triangulation. Optionally, this technique may be also used to determine velocity and/or attitude of the vehicle.

By determining three-dimensional positions of the vehicle at two successive times, the navigation system <NUM> is also configured to determine vehicle velocity. Based upon vehicle three-dimensional position and velocity, the navigation system <NUM> is also configured to determine if the vehicle <NUM> is on a collision course with an obstacle <NUM>. If the vehicle <NUM> is on a collision course with an obstacle <NUM> detected by the radar(s), then the navigation system <NUM> is configured to control the flight controls and actuators <NUM> to change the course of the vehicle <NUM> to avoid collision with the obstacle <NUM>.

In the example shown in <FIG>, the communications system <NUM> is coupled to the navigation system <NUM>. The communications system <NUM> can include one or more respective computing circuits, such as a microprocessor or microcontroller, and respective other circuits, such as peripheral circuits and sensors. The computing circuits and other circuits can be configured with firmware or other configuration data, programmed with software, or hardwired to perform certain functions and tasks related to the flying, monitoring, flight-application processing, and maintenance of the vehicle <NUM>. For example, each of one or more of the computing circuits can execute one or more software applications to implement the functions of the corresponding subsystem. Although not shown in <FIG>, the communication system <NUM> optionally includes an Aeronautical Operation Control ("AOC") data engine, which is configurable by a loadable AOC database (not shown in <FIG>), and which provides the communications system <NUM> with the ability to communicate with systems, subsystems, and human/machine interfaces (both onboard and off board the vehicle <NUM>). For example, the communications system <NUM> can be configured receive and transmit data to other locations as further described elsewhere herein.

<FIG> is a block diagram of one example of a navigation system <NUM>. The description of components with similar names and numbering (i.e. the navigation system <NUM>) applies to the previous iterations of the components, and vice versa.

The navigation system <NUM> is configured to operate on and/or in the vehicle <NUM>. The navigation system <NUM> uses radar return image(s) in conjunction with three-dimensional maps to assist with navigation of the vehicle <NUM>. The navigation system <NUM> includes a processing system <NUM> including a three-dimensional map database <NUM> and coupled to a GNSS receiver <NUM>. For example, the GNSS receiver <NUM> may be a GPS receiver. The processing system <NUM> is configured to be coupled to radar(s) (e.g. the forward-facing radar <NUM> and the downward-facing radar <NUM>), and the flight controls and actuators <NUM>.

Optionally, the navigation system <NUM> includes an air data unit <NUM> and/or an AHRS <NUM> which are coupled to the processing system <NUM>. The air data unit <NUM> is configured to provide data to the processing system <NUM> about the vehicle's altitude above the ground or sea level. The AHRS <NUM> is configured to provide data to the processing system <NUM> system about heading and attitude (including roll, pitch, and yaw) of the vehicle <NUM>; such information can be used to determine vehicle three-dimensional position and velocity. An AHRS <NUM> is typically much less expensive than an IMU. Attitude of the vehicle <NUM> means the orientation of the vehicle <NUM> with respect to the inertial frame of reference of the three-dimensional map database <NUM> (e.g. with respect to the Earth).

The processing system <NUM> is configured receive data about the three-dimensional position, attitude, and/or velocity of the vehicle from the GNSS receiver <NUM>, and possibly the air data unit <NUM> and/or the AHRS <NUM>. When available, this data can be used to determine at least the three-dimensional position and/or velocity of the vehicle <NUM>. Based upon knowing the three-dimensional position of the vehicle <NUM>, the processing system <NUM> can guide the vehicle <NUM> so that it does not collide with an obstacle <NUM>, e.g. a building, identified in the three-dimensional map database <NUM> and/or in radar return image(s). To do so, the processing system <NUM> is configured generate control signals. The flight control actuators <NUM> are configured to be coupled to the processing system <NUM> and to receive the control signals. With knowledge of the vehicle's three-dimensional position, the navigation system <NUM> can modify the velocity, and thus the future three-dimensional position, of the vehicle <NUM> to avoid collision(s) with obstacle(s).

The vehicle <NUM> primarily uses the GNSS receiver <NUM> to determine its three-dimensional position and velocity. Optionally, the processing system <NUM> can determine three-dimensional position and velocity using both three-dimensional position data from the GNSS receiver <NUM> and three-dimensional position data derived by correlating radar return image(s) with the three-dimensional map database <NUM>; the three-dimensional position data from the GNSS receiver <NUM> is used to determine which data in the three-dimensional map database <NUM> should be correlated with the radar return image(s) so as to more efficiently determine position using the radar return image(s). Using data from both the GNSS receiver <NUM> and the aforementioned correlation can be used to generate more accurate three-dimensional position and/or velocity data, and/or to identify obstacles <NUM> not present in the three-dimensional map database <NUM>. A combination of GNSS receiver position data and position data using correlation of radar return images may be used, e.g. with Kalman filters in and executed by the processing system <NUM>, to more accurately determine three-dimensional position and/or the velocity of the vehicle <NUM>. Also, the radar(s) may be used to detect and avoid collisions with objects <NUM> not identified in the three-dimensional map database. Upon determining the three-dimensional positions of the surfaces of newly detected stationary objects, e.g. buildings or other structures, such information can be added to the three-dimensional map database <NUM>; updating the three-dimensional map database will be subsequently described.

Optionally, data from the correlation of measured radar return images with the three-dimensional map database <NUM>, the GNSS receiver <NUM>, and even from the air data unit <NUM> and/or the AHRS <NUM> may be combined to more accurately determine the position, velocity, and attitude of the vehicle <NUM>. Optionally, Kalman filter(s) in and executed by the processing system <NUM> may be utilized to more accurately obtain such three-dimensional position and/or the velocity of the vehicle <NUM>. By more accurately determining three-dimensional position and velocity of a vehicle, the subsequently described margin of error may be reduced. Thus, more vehicles using this technique can travel in the same region, e.g. air space.

As discussed above GNSS signals may be diminished by various mechanism. If the GNSS signals are diminished (e.g. one or more satellite signals are lost), the accuracy of the position and velocity data provided by the GNSS receiver <NUM> are diminished and is neither accurate enough to be relied upon to avoid a collision with an obstacle nor will it be able to safely land. The vehicle may crash, e.g. by running out of power when trying to determine its position using GNSS position data. Embodiments of the invention mitigate these risks, particularly in urban environments.

Thus, if for example, an accuracy level of the GNSS receiver <NUM> is diminished, e.g. below a predefined threshold so that the navigation cannot sufficiently accurately determine its location, the navigation system <NUM> can utilize correlation of radar return image(s) with the three-dimensional map database <NUM> (in lieu of or in conjunction with other position determining systems such as a GNSS receiver) to determine the position of the vehicle <NUM>.

For example, the correlation of radar return image(s) with the three-dimensional map database <NUM> can be used to validate the GNSS position on a map and to determine the accuracy level of the GNSS receiver <NUM>. For example, SAR or ISAR images can be correlated to an optically imaged map. When signals are degraded due to lost satellite signals, the GNSS receiver <NUM> can determine the accuracy of its three-dimensional position data and/or its velocity data. The predefined threshold may be determined by a system designer and/or by regulation. The three-dimensional position data from the GNSS receiver <NUM> last received when the accuracy level is less than the predefined level is used to ascertain which portion of the three-dimensional map database <NUM> should be initially compared to the radar return image(s).

The radar(s) are configured to be coupled to a processing system <NUM>. When utilized, each radar is configured to periodical provide at least one radar return image to the processing system <NUM>. The processing system <NUM> is configured to receive each of such at least one radar return images. The processing system <NUM> is configured to correlate each set of periodically provided radar return images with the three-dimensional map database <NUM>, and to attempt to determine the three-dimensional position and the velocity of the vehicle <NUM>.

The processing system <NUM> comprises processing circuitry coupled to memory circuitry. The processing system <NUM> may be implemented with analog and/or digital circuitry. For example, the processing circuitry may be implemented with electronic analog circuitry, including circuitry used to implement electronic analog computers. In some examples, the processing system <NUM> is configured to correlate the output of radar(s) with data of the three-dimensional map database <NUM>, the air data unit <NUM>, the AHRS <NUM>, and the GNSS receiver <NUM>. In some examples, the processing system <NUM> is incorporated into the other components within the navigation system <NUM>.

The three-dimensional map may or may not be stored in memory circuitry of the processing system <NUM>. In some examples, the three-dimensional map database (also hereinafter referred to as "map database") <NUM> comprises one or more of the following types of maps:.

In other examples, the three-dimensional map database <NUM> is periodically created with radar image returns from by one or more radars stationary in or moving around an environment, e.g. urban environment. For example, a vehicle such as that described with respect to <FIG> and <FIG> may be used to periodically generate radar return images of the environment and to periodically create a three-dimensional map database. Optionally, the periodically created three-dimensional map database is stored in a computer system (e.g. a server system or cloud computing system) outside of the vehicle <NUM> and is uploaded periodically to the vehicle <NUM>.

In some examples, the three-dimensional map database <NUM> can be updated by the processing system <NUM> with radar return images generated by radar(s) on the vehicle <NUM>, and optionally in conjunction with information from the components on the vehicle <NUM>. In one example, when the vehicle <NUM> travels, the radar(s) sense the environment about the vehicle <NUM>. The processing system <NUM> may not only determine position of a vehicle <NUM> based upon correlation (or alternatively position data is determined using data from other component(s) such as the GNSS receiver <NUM>), but also can identify an obstacle in radar return image(s) not included in the map database <NUM>. When radar(s) detect an object not found in the map database <NUM>, the navigation system <NUM> can determine whether the object is stationary in position or moving, e.g. another moving vehicle. For example, this can be achieved by evaluating whether the object is moving by determining if its absolute position changes over time or by evaluating the Doppler shift of radar return signal(s) reflected by the object. Cooperative systems, e.g. data from a traffic collision avoidance system and/or an automatic dependent surveillance-broadcast, can be combined with the three-dimensional map database to assist in determination as to whether an object is moving or not. If the object is stationary, the navigation system <NUM> can add information about the obstacle, e.g. the radar return image of the obstacle, to a three-dimensional map database <NUM> and/or as an alert or a notification to an internal or external system that a new stationary object has been located. Subsequently, when the vehicle <NUM> travels near the object at another time, the navigation system <NUM> can plan in advance a path of the vehicle <NUM> that circumvents the object. Further, the navigation system <NUM> can communicate the updated three-dimensional map database (or just a change to the three-dimensional map database <NUM> corresponding to the object) with other vehicles and/or a central map database, e.g. in a server or cloud computer system, so that other vehicles can use such data for navigation.

In the example shown in <FIG>, the radar return images <NUM> are stored within the processing system <NUM>. It is understood that the radar return images <NUM> can be stored within another system within the vehicle and/or within an external system. In some examples, the radar return images <NUM> are stored in memory circuitry. The radar return images <NUM> comprise radar return signals from the radars <NUM>, <NUM> that have been processed to create images of the environment surrounding the vehicle <NUM>.

In the example shown in <FIG>, the correlation unit <NUM> is also stored within the processing system. The correlation unit <NUM> is configured to compare and correlate the radar return images <NUM> with the three-dimensional map database <NUM>. If the correlation unit <NUM> identifies an obstacle in a radar return image that is not found in the three-dimensional map database <NUM>, the correlation unit <NUM> or another component of the navigation system <NUM> can add the obstacle to the three-dimensional map database <NUM>.

In the example shown in <FIG>, the air data unit <NUM> is configured to be coupled to the processing system <NUM> and to provide an altitude of the vehicle <NUM>, and optionally a rate of change of the altitude of the vehicle <NUM>. In some examples, the air data unit <NUM> comprises a baro-altimeter which provides information about the altitude above ground or sea level of the vehicle <NUM> based the barometric pressure measured by the baro-altimeter. In some examples, the known altitude of the vehicle <NUM> reduces number of comparisons of the radar return image(s) with the three-dimensional map database, as one of the three axes is known. For example, while the air data unit <NUM> determines that the altitude of the vehicle <NUM> is above a maximum altitude of all obstacles in a region in which the vehicle <NUM> is travelling (or above a maximum altitude plus an offset amount), then the navigation system <NUM> and the processing system <NUM> need not utilize data from radar(s) <NUM>, <NUM> in performance of a navigation function. The offset value may be used to account for a margin of error in measurement data from the air data unit <NUM>. Furthermore, if the vehicle does not detect obstacles in its path, e.g. the vehicle is above a maximum altitude of all obstacles, the navigation system <NUM> can be configured to adjust scanning strategy, e.g. to focus on detecting and avoiding other moving objects or switch to long range scanning and/or mapping.

In the example shown in <FIG>, AHRS <NUM> provides information to the other components about the attitude and heading of the vehicle <NUM>. In some examples, the AHRS <NUM> includes at least one accelerometer, at least one gyroscope, and at least one magnetometer. Each accelerometer measures acceleration along an axis. Each gyroscope measures angular rotation around an axis. Each magnetometer determines direction of an ambient magnetic field. The data from the AHRS <NUM> may be used to determine that attitude of the vehicle <NUM>, and thus the orientation of radar(s) on the vehicle <NUM> with respect to the three-dimensional database <NUM>.

When the vehicle <NUM> is oriented off axis, the radar return image must be corrected with attitude information before correlation with the three-dimensional map database <NUM>. The processing system <NUM> uses the output of the inertial measurement unit <NUM> to determine the attitude and/or heading of the vehicle <NUM> with respect to the inertial frame of reference of the three-dimensional map database <NUM> (e.g. with respect to the Earth) and align the radar return image with the three-dimensional map database <NUM> so that they have the same frame of reference.

Optionally, data from the AHRS <NUM>, the GNSS receiver <NUM>, the air data unit <NUM>, the correlation of measured radar return images with the map database <NUM> may be combined to more accurately determine the three-dimensional position, velocity, and attitude of the vehicle <NUM>. Optionally, Kalman filter(s) executed on the processing system <NUM> may be utilized to obtain more accurate results.

In the example shown in <FIG>, the GNSS receiver <NUM> is configured to provide the three-dimensional position, and optionally the velocity, of the vehicle <NUM> and time when adequate signals from the GNSS are available. When the vehicle <NUM> is within an urban environment, GNSS satellite reception may be diminished. Thus, the three-dimensional position of the vehicle <NUM> provided by the GNSS receiver <NUM> may not be accurate or unavailable. When deprived of accurate three-dimensional position data, e.g. from the GNSS receiver <NUM>, the navigation system <NUM> relies upon correlating the radar return images with the map database <NUM> to obtain such information. Three-dimensional position data is determined using three-dimensional position data derived from the correlation process alone or in conjunction with other data such as three-dimensional position data from the GNSS receiver <NUM>.

For example, when the accuracy of the three-dimensional position data from GNSS receiver <NUM> is determined to exceed a threshold level, the navigation system <NUM> relies upon such correlation to determine vehicle position, trajectory, and/or velocity, and thus vehicle navigation guidance. Optionally, when the accuracy of the position data of the GNSS receiver <NUM> exceeds the threshold level, the navigation system <NUM> may use a combination of other data, e.g. from the GNSS receiver <NUM>, the air data unit <NUM>, and/or the AHRS <NUM>, with the three-dimensional position data derived from the radar image return correlation(s), e.g. using Kalman filters, to determine vehicle three-dimensional position and/or velocity. For illustrative purposes only, the threshold level may be one meter, and the accuracy of the position data may be two meters; in such a case, the accuracy exceeds the threshold level. Thus, the vehicle <NUM> may be guided using this data from more than one sensor on the vehicle <NUM>.

If, optionally, the navigation system <NUM> does not include a GNSS receiver <NUM> (or if the GNSS receiver <NUM> is not functioning), the aforementioned options of utilizing radar return image correlations or the combination of other data (e.g. from the air data unit <NUM> and/or the AHRS <NUM>) with radar return image correlations may be used to determine vehicle three-dimensional position and/or velocity. Thus, the vehicle <NUM> may be guided using this data from more than one sensor (excluding a GNSS receiver <NUM>) on the vehicle <NUM>.

In the example shown in <FIG>, the flight controls and actuators <NUM> are configured to be coupled to the processing system <NUM>, and to affect a change of velocity and thus position of the vehicle <NUM>. The flight controls and actuators <NUM> include, for example, control surface(s) of the vehicle <NUM> and propulsion system(s) of the vehicle <NUM>, and systems for controlling the foregoing. The control surfaces may include wheel(s), elevator(s), aileron(s), and/s rudder(s). The propulsion systems may include electric motors and/or engines coupled to propellers.

The vehicle <NUM> may be autonomously controlled by the navigation system <NUM> as described above. In this case, the flight controls and actuators <NUM> receive information from the processing system <NUM> to control the velocity and attitude of the vehicle <NUM>. As a result, the navigation system <NUM> can maneuver the vehicle <NUM> to an intended destination but away from an obstacle <NUM> with which the vehicle <NUM> is on a collision path. For example, the obstacle <NUM> may be detected by radar(s).

Alternatively, the vehicle <NUM> may be controlled by a human operator(s), e.g. pilot(s). When the vehicle <NUM> is operated by a human pilot(s), the flight controls and actuators <NUM> are accessible to the human operator(s) and may also include displays. The human operator(s), and thus the displays, may be in the vehicle <NUM> or remotely located from the vehicle such as on the ground or in another vehicle. Such displays display data such as vehicle position, obstacle positions near the vehicle <NUM>, velocity, attitude, etc. Such position information may include altitude and/or lateral position. Further, the flight controls and actuators <NUM> include controls, such as pedal(s), stick(s), and/or yoke(s) for the human operator(s) to provide input to control the position, velocity, and attitude of the vehicle <NUM>.

<FIG> illustrates an exemplary process <NUM> for performing vehicle position determination using at least one radar. The process <NUM> is illustrated in <FIG> and described herein as comprising discrete elements. Such illustration is for ease of description and it should be recognized that the function performed by these elements may be combined in one or more components, e.g. implemented in software and/or hardware.

To the extent the method <NUM> shown in <FIG> is described herein as being implemented in the devices described above with respect to <FIG> and <FIG>, it is to be understood that other embodiments can be implemented in other ways. The blocks of the flow diagrams have been arranged in a generally sequential manner for ease of explanation; however, it is to be understood that this arrangement is merely exemplary, and it should be recognized that the processing associated with the methods (and the blocks shown in the Figures) can occur in a different order (for example, where at least some of the processing associated with the blocks is performed in parallel and/or in an event-driven manner).

Optionally, in block <NUM>, determine if a three-dimensional position accuracy determined by at least one sensor (excluding radar) on a vehicle exceeds a threshold level. The at least one sensor may be a GNSS receiver <NUM> and/or an air data unit <NUM>. For example, if the accuracy of the three-dimensional position exceeds the threshold level, then the at least one sensor (excluding radar) may not be able to safely navigate the vehicle. If the three-dimensional position accuracy does not exceed the threshold level, then return to block <NUM>. If the three-dimensional position accuracy exceeds a threshold level, then proceed to block <NUM>.

In block <NUM>, project at least one directional beam from at least one radar on the vehicle, where each radar periodically emits a radar signal in each directional beam and may receive a radar return signal in the directional beam. Optionally, scan at least a portion of a field of regard of at least one radar with at least one of the at least one directional beam. For example, a single radar (such as a forward-facing radar) may scan a directional beam using progressive scanning. However, other scanning techniques may be used, such as interlaced scanning of two directional beams emitted by one or more radars. If the directional beam is not scanned, then for example the directional beam may be fixedly pointed, at least for a period of time, at a specific region in the field of regard of the radar which can provide obstacle detection in the corresponding field of view and determination of distance from the obstacle.

In block <NUM>, generate at least one radar return image from the reflected radar signals in the at least one directional beam for the corresponding at least a portion of the field of regard of a corresponding radar for a period of time T. Optionally, the navigation system determines the portion(s) of the field of regard to be imaged by a radar.

For example, if the directional beam is being scanned, the radar return image may be formed over N scans of the selected at least a portion of the field of regard during time period T, where N is an integer greater than zero. In some examples, the radar(s) and/or the navigation system generates the radar return image from the radar return signals.

In block <NUM>, correlate at least one radar return image with a three-dimensional map database, e.g. using image processing techniques. The radar return image is correlated to the three-dimensional map database to ascertain whether the radar return image data is statistically similar to a region of the three-dimensional map database. Optionally, correlation may be more efficiently performed if the position of the vehicle can be estimated based upon past correlations and/or data from other components as described above. Optionally, the location can be more accurately determined when using data from other components as described above.

Optionally, in block <NUM>, determine if the radar return image includes at least one stationary object not included in the three-dimensional map database. If the radar return image includes at least one stationary object not included in the three-dimensional database, then in optional block <NUM>, add the at least one stationary object to the three-dimensional map database, and continue to block <NUM>. If the radar return image does not include at least one stationary object not included in the three-dimensional map database, then continue to block <NUM>.

In block <NUM>, determine at least one of a three-dimensional position and a velocity of the vehicle using the correlation. Determine the three-dimensional position by determining the vector distance of the vehicle from three-dimensional locations of surfaces of obstacles determined to be proximate to the vehicle by the correlation. The three-dimensional position of the vehicle is determined more accurately by accounting for the attitude of the vehicle and the distance of the vehicle from sensed objects. The attitude of the vehicle can be determined, for example, with an AHRS. The vector distance from a surface of an obstacle proximate to the vehicle can be determined with radar(s), e.g. based upon the one half of the time between transmission of a radar signal and reception of the corresponding radar return signal. The velocity can be calculated by determining the change in three-dimensional position from the last calculated three-dimensional position and the current three-dimensional position, divided by the time between the two position determinations.

Optionally, in block <NUM>, determine if the vehicle is on a collision course with at least one obstacle, e.g. detected in at least one radar return image. This is accomplished by determining the future path of the vehicle based upon its current velocity, and whether there is an obstacle in the future path. The obstacle(s) may be sensed by radar(s) on the vehicle and/or in the map database in the vehicle. The location of obstacle(s) sensed by radar(s), but not in the map database, can be determined based upon vehicle position and attitude, one half of the time delay between transmitting a radar signal and the radar signal reflected from each object, and the radar beam angle at which the object is detected Because the vehicle position and velocity, and obstacle positions are known or determined, obstacle(s) in the trajectory of the vehicle can be readily determined. In some examples, the trajectory of the vehicle includes area volume around the vehicle which represents the volume of the vehicle and/or a margin of error. Thus, determining a collision course comprises determining if the volume will intersect at least one obstacle.

In some embodiments, the at least one obstacle are stationary obstacle(s). However, in other embodiments, the at least one obstacle are stationary and moving obstacle(s). In such embodiments, determine the path of the moving obstacles and whether any of the moving obstacles will collide with the vehicle.

In block <NUM>, if the vehicle is determined to be on a collision course with at least one obstacle, optionally in block <NUM> generate at least one path to avoid collision(s) with at least one obstacle. Optionally, select one path and change the path of travel of the vehicle to avoid the such obstacle(s) by following the selected path. trajectory of the vehicle can be readily determined. In some examples, the trajectory of the vehicle includes area volume around the vehicle which represents the volume of the vehicle and/or a margin of error. Thus, determining a collision course comprises determining if the volume will intersect at least one obstacle.

In block <NUM>, if the vehicle is determined to be on a collision course with at least one obstacle, optionally in block <NUM> generate at least one path to avoid collision(s) with at least one obstacle. Optionally, select one path and change the path of travel of the vehicle to avoid the such obstacle(s) by following the selected path. This is accomplished, e.g. by increasing or decreasing vehicle altitude, changing vehicle lateral position, changing vehicle speed, and/or changing vehicle direction. Practically, the foregoing is affected by manually and/or automatically changing the vehicle's flight controls and actuators. When the vehicle is automatically controlled, a navigation system (in or not in the vehicle) generates control signals to change the vehicle's flight controls so that the vehicle automatically avoids collisions.

Claim 1:
A system comprising:
a Global Navigation Satellite System (GNSS) receiver (<NUM>) configured to receive signals from satellites of the GNSS and to be installed on a vehicle (<NUM>);
a processing system (<NUM>), where the memory circuitry comprises a three-dimensional map database;
wherein the processing system is configured to:
determine if the accuracy of position data provided by the GNSS receiver is greater than a threshold level; and only if the accuracy of the position data is greater than the threshold level, the processing system is configured to:
receive at least one radar return image;
correlate the at least one radar return image with the three-dimensional map database (<NUM>), wherein three-dimensional position data last received from the GNSS receiver when the accuracy was below the threshold level is used to determine a portion of the three-dimensional map database for comparison with the radar return image; and
determine, based upon the correlation, at least one of a three-dimensional position and a velocity of the vehicle.