Navigation device and method of operating the same

Abstract

A method for operating a navigation device includes: obtaining valid global positioning system (GPS) data at a current time point corresponding to a current position of a target device; determining a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current time point from a plurality of map elements of the map data; and determining a posture parameter of the target device at the current time point based on a first direction specified by at least a portion of the first adjacent map element.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority from Korean Patent Application No. 10-2019-0144100 filed on November 12, 2019, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein in its entirety for all purposes by reference. Technical Field

[0003] The following description relates to a navigation device and a method of operating the navigation device. Background Art

[0004] Existing navigation devices can provide information associated with the direction in which a vehicle is traveling or travelling, as well as the vehicle's position, by receiving information associated with the position via a global positioning system (GPS) and matching the received information with a two-dimensional (2D) map. To match the received information with the 2D map, there are methods that calculate the distance between the vehicle's position obtained by GPS and its position on a road link and match the vehicle's position with the position on the road link that is shortest from the vehicle's position; or there are methods that estimate the direction based on road geometry information, road junction information, and the rotation angle of each node, and match the estimated direction with the map. The accuracy level of such existing navigation devices can depend on this matching technology, and therefore a high level of accuracy can be associated with an accurate match. Summary of the Invention

[0005] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0006] In one general aspect, a method for operating a navigation device includes: obtaining valid global positioning system (GPS) data at a current point in time corresponding to a current position of a target device; determining a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current point in time from a plurality of map elements of the map data; and determining a posture parameter of the target device at the current point in time based on a first direction specified by at least a portion of the first adjacent map element.

[0007] The first direction may be a three-dimensional (3D) direction.

[0008] The attitude parameters may include a roll parameter, a pitch parameter, and a yaw parameter.

[0009] Determining the posture parameter of the target device at the current time point based on the first direction may include identifying the first direction by performing line fitting on a plurality of points included in the first adjacent map element and respectively corresponding to 3D positions.

[0010] Determining the posture parameters of the target device at a current point in time based on the first direction may include: determining a GPS-based yaw based on valid GPS data at the current point in time and a position of the target device at a previous point in time; and extracting samples from the first-neighboring map elements by comparing the map-based yaw corresponding to each of the first-neighboring map elements with the determined GPS-based yaw.

[0011] Determining the posture parameter of the target device at the current time point based on the first direction may further include: identifying the first direction by applying a random sample consensus (RANSAC) algorithm to the extracted samples.

[0012] Determining a posture parameter of the target device at a current time point based on the first direction may include determining the posture parameter by comparing a sensor-based yaw at the current time point with a map-based yaw corresponding to the first direction. The sensor-based yaw at the current time point may be calculated by applying a yaw rate measured by a steering sensor of the target device to a yaw of the target device at a previous time point.

[0013] The pose parameter may be determined to correspond to the first direction in response to a difference between the sensor-based yaw and the map-based yaw being less than a threshold.

[0014] The operating method may also include: determining a direction cosine matrix (DCM) corresponding to the determined posture parameters of the target device at the current time point; and determining the speed parameters of the target device at the current time point by applying the DCM to a speed vector corresponding to the speed of the target device at the current time point, wherein the speed is measured by a speed sensor of the target device.

[0015] The operating method may further include: determining a map-based lane by matching valid GPS data at a current point in time with map data; determining a sensor-based lane by applying a lane change trigger factor to a sensor-based position of the target device at the current point in time, wherein the sensor-based position is calculated by applying dead reckoning (DR) to a position of the target device at a previous point in time; and determining a position parameter of the target device at the current point in time by comparing the map-based lane and the sensor-based lane.

[0016] The operating method may further include generating a lane change trigger factor by comparing a lane width with a position change of the target device in a lateral direction.

[0017] The operating method may also include determining whether valid GPS data has been obtained.

[0018] Determining whether valid GPS data is obtained includes: obtaining GPS data at a current time point corresponding to a current location of the target device; determining a GPS-based speed and a GPS-based yaw rate based on the obtained GPS data at the current time point; obtaining a sensor-based speed measured by a speed sensor of the target device and a sensor-based yaw rate measured by a steering sensor of the target device; and determining validity of the GPS data based on a result of comparing the GPS-based speed with the sensor-based speed and a result of comparing the GPS-based yaw rate with the sensor-based yaw rate.

[0019] In another general aspect, a non-transitory computer-readable storage medium stores instructions that, when executed by a processor, cause the processor to perform the operations described above.

[0020] In another general aspect, a method of operating a navigation apparatus includes: in response to not obtaining valid global positioning system (GPS) data at the current point in time corresponding to the current position of a target device, obtaining a sensor-based position at the current point in time, the sensor-based position at the current point in time being calculated by applying dead reckoning (DR) to a previous position of the target device and corresponding to the current position of the target device; determining, from a plurality of map elements, an adjacent map element corresponding to an area indicated by the sensor-based position at the current point in time; and determining a pose parameter of the target device at the current point in time based on a direction specified by at least a portion of the adjacent map element.

[0021] Determining the posture parameter of the target device at the current time point based on the direction may include identifying the direction by performing line fitting on a plurality of points included in adjacent map elements and respectively corresponding to 3D positions.

[0022] Determining the posture parameter of the target device at the current time point based on the direction may include: identifying the direction by applying a RANSAC algorithm to adjacent map elements.

[0023] Determining the posture parameters of the target device at a current point in time based on the direction may include: determining pitch and roll among the posture parameters based on the direction; and determining yaw among the posture parameters by applying a yaw rate measured by a steering sensor of the target device to the yaw of the target device at a previous point in time.

[0024] In another general aspect, a navigation device includes a processor configured to: obtain valid global positioning system (GPS) data at a current point in time corresponding to a current location of a target device; determine a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current point in time from a plurality of map elements of the map data; and determine a posture parameter of the target device at the current point in time based on a first direction specified by at least a portion of the first adjacent map element.

[0025] The processor may be further configured to identify the first direction by performing line fitting on a plurality of points included in the first adjacent map element and respectively corresponding to three-dimensional (3D) positions.

[0026] The processor may also be configured to: determine a GPS-based yaw based on valid GPS data at a current point in time and a location of the target device at a previous point in time; and extract samples from the first-neighboring map element by comparing a map-based yaw corresponding to each of the first-neighboring map elements with the determined GPS-based yaw.

[0027] The processor may be further configured to identify the first direction by applying a Random Sample Consensus (RANSAC) algorithm to the extracted samples.

[0028] The processor may be further configured to determine the pose parameter by comparing the sensor-based yaw at a current point in time with the map-based yaw corresponding to the first direction. The sensor-based yaw at the current point in time may be calculated by applying a yaw rate measured by a steering sensor of the target device to the yaw of the target device at a previous point in time.

[0029] In response to a difference between the sensor-based yaw and the map-based yaw being less than a threshold, it is determined that the pose parameter corresponds to a first direction.

[0030] The processor may also be configured to, in response to not obtaining valid GPS data at the current point in time: obtain a sensor-based position at the current point in time, the sensor-based position at the current point in time being calculated by applying dead reckoning (DR) to a previous position of the target device and corresponding to the current position of the target device; determine a second adjacent map element corresponding to a second area indicated by the obtained sensor-based position at the current point in time from a plurality of map elements; and determine a posture parameter of the target device at the current point in time based on a second direction specified by at least a portion of the second adjacent map element.

[0031] The processor can also be configured to: determine a direction cosine matrix (DCM) corresponding to the determined posture parameters of the target device at the current time point; and determine the speed parameters of the target device at the current time point by applying the DCM to a speed vector corresponding to the speed of the target device at the current time point, wherein the speed is measured by a speed sensor of the target device.

[0032] The processor may be further configured to: determine a map-based lane by matching valid GPS data at a current point in time with map data; determine a sensor-based lane by applying a lane change trigger factor to a sensor-based position of the target device at the current point in time, wherein the sensor-based position is calculated by applying dead reckoning (DR) to a position of the target device at a previous point in time; and determine a position parameter of the target device at the current point in time by comparing the map-based lane and the sensor-based lane.

[0033] The processor may be further configured to generate a lane change trigger factor by comparing a change in position of the target device in a lateral direction to a lane width.

[0034] The navigation device may further include a memory storing instructions, wherein the processor is configured to execute the instructions to obtain valid Global Positioning System (GPS) data, determine a first adjacent map element, and determine a pose parameter.

[0035] Other features and aspects will become apparent from the following detailed description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a diagram showing an example of input and output of a navigation device.

[0037] Figure 2 is a diagram showing an example of posture parameters.

[0038] Figure 3 is a diagram showing an example of the operation of the navigation device.

[0039] Figure 4 is a diagram illustrating an example of determining the validity of Global Positioning System (GPS) data.

[0040] Figure 5 is a diagram showing an example of map data.

[0041] Figure 6 is a diagram showing an example of determining posture parameters.

[0042] Figure 7 is a diagram showing an example of determining speed parameters.

[0043] Figure 8 is a diagram showing an example of determining position parameters.

[0044] Figure 9 is a diagram illustrating an example of determining a lane change.

[0045] Figure 10 is a flowchart illustrating an example of an operating method of a navigation device.

[0046] Figure 11 is a diagram showing an example of the configuration of a navigation device.

[0047] Throughout the drawings and detailed description, like reference numerals refer to like elements, features, and structures. The drawings may not be drawn to scale, and the relative sizes, proportions, and depictions of elements in the drawings may be exaggerated for clarity, illustration, and convenience. DETAILED DESCRIPTION

[0048] The following detailed description is provided to help the reader obtain a comprehensive understanding of the methods, devices and / or systems described herein. However, after understanding the disclosure of the present application, various changes, modifications and equivalents of the methods, devices and / or systems described herein will be apparent. For example, the order of operations described herein is merely an example and is not limited to those order of operations set forth herein, but may be significantly changed after understanding the disclosure of the present application, except for operations that must be performed in a certain order. In addition, for greater clarity and brevity, the description of known features may be omitted after understanding the disclosure of the present application.

[0049] The features described herein may be implemented in different forms and should not be construed as limited to the examples described herein. Rather, the examples described herein are provided merely to illustrate some of the many possible ways to implement the methods, devices, and / or systems described herein, which will become apparent upon understanding the disclosure of this application.

[0050] Note that in this document, use of the term "may" with respect to an example or embodiment (e.g., with respect to what an example or embodiment may include or implement) means that there is at least one example or embodiment that includes or implements such feature, and all examples and embodiments are not limited thereto.

[0051] Throughout the specification, when an element such as a layer, region, or substrate is described as being "on," "connected to," or "coupled to" another element, it can be directly "on," "connected to," or "coupled to" the other element, or one or more other elements may be present in between. Conversely, when an element is described as being "directly on," "directly connected to," or "directly coupled to" another element, there may not be any other elements in between. As used herein, the term "and / or" includes any one and any combination of any two or more of the associated listed items.

[0052] Although terms such as "first," "second," and "third" may be used herein to describe various components, assemblies, regions, layers, or portions, these components, assemblies, regions, layers, or portions should not be limited by these terms. Instead, these terms are merely used to distinguish one component, component, region, layer, or portion from another component, component, region, layer, or portion. Thus, a first component, component, region, layer, or portion mentioned in the examples described herein may also be referred to as a second component, component, region, layer, or portion without departing from the teachings of the examples.

[0053] The terms used herein are only used to describe various examples and are not intended to limit the present disclosure. Unless the context clearly indicates otherwise, the articles "a", "an" and "the" are also intended to include plural forms. The terms "include", "comprising" and "having" indicate the presence of the recited features, numbers, operations, components, elements and / or combinations thereof, but do not preclude the presence or addition of one or more other features, numbers, operations, components, elements and / or combinations thereof.

[0054] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art based on their understanding of the disclosure of this application. Terms such as those defined in commonly used dictionaries should be interpreted as having the same meaning as in the context of the relevant technology and / or this application, and should not be interpreted as having an ideal or overly formal meaning unless explicitly defined herein.

[0055] Additionally, in the description of the exemplary embodiments, detailed descriptions of structures or functions known therefrom after understanding the present application may be omitted.

[0056] Figure 1 is a diagram showing an example of input and output of a precision navigation device.

[0057] Reference Figure 1The precise navigation device 100 (hereinafter, "navigation device 100") can provide precise information associated with the physical state of the target device. For example, the navigation device 100 can provide navigation parameters indicating any one or any combination of any two or more of attitude, speed, and position based on any one or any combination of any two or more of speed data, steering data, global positioning system (GPS) data, and map data. In this example, the steering data may include steering angle data.

[0058] The target device may include various devices that may require accurate status information. For example, the target device may be one of various types of augmented reality (AR) devices, including, for example, an augmented reality head-up display (AR HUD) device, a vehicle including an AR HUD, a mobile device that provides AR, etc. The AR device may display a real background overlaid with a virtual image based on the state of the AR device. In order to accurately reflect the AR environment, the AR device may need to accurately measure the state of the AR. For another example, the target device may be an autonomous driving vehicle that requires precise positioning.

[0059] Navigation parameters can be used in a variety of applications. For example, they can be used to provide navigation information to users and control driving for autonomous vehicles. In one example, navigation parameters can be used as initialization for sensor fusion. Sensor fusion is a method that combines multiple different types of sensors into a single solution. For example, sensor fusion can be used to determine a vehicle's attitude, velocity, and position.

[0060] When the output of sensor fusion converges to the true value, sensor fusion can produce a relatively accurate output. However, when initial information with a relatively large error is provided to sensor fusion, it may take a relatively long time period for the output of sensor fusion to converge to the true value. For example, in this case, the AR device may not be able to match the virtual image with the real background within such a long time period. The navigation device 100 can generate relatively accurate navigation parameters, and the generated accurate navigation parameters can be used in the initial terms of sensor fusion to improve the performance of sensor fusion in terms of accuracy. For example, the navigation parameters of the navigation device 100 can be used as initial information for sensor fusion and then provided for sensor fusion within a period of time until the output of sensor fusion converges to the true value.

[0061] As described above, the navigation device 100 can use speed data, steering data, GPS data, and map data to generate navigation parameters. For example, the map data used here can be based on a high-definition (HD) map. The HD map may include information associated with various elements (e.g., lanes, center lines, and traffic signs or markings) generated based on various sensors. These various elements of the HD map can be represented by a point cloud, and each point in the point cloud can correspond to a three-dimensional (3D) position. The navigation device 100 can use such an HD map to generate accurate navigation parameters including 3D attitude, 3D speed, and lane horizontal position.

[0062] In addition, the speed data, steering data, and GPS data used to generate navigation parameters can be obtained by speed sensors, steering sensors, and GPS receivers commonly used in vehicles or mobile devices. The speed sensor may include, for example, an odometer. The steering sensor may include, for example, a steering wheel and a gyroscope. Therefore, the precise navigation system 100 may not require some additional and expensive sensors, such as light detection and ranging (LiDAR) sensors.

[0063] Figure 2 is a diagram showing an example of posture parameters. Figure 2 , showing an xyz 3D coordinate space. The posture parameters may include a roll parameter, a pitch parameter, and a yaw parameter. The roll parameter may indicate the tilt relative to the x-axis. The pitch parameter may indicate the tilt relative to the y-axis. The yaw parameter may indicate the tilt relative to the z-axis. For example, the x-axis may correspond to the direction in which the target device is traveling or moving.

[0064] The attitude of the target device can be represented by a line corresponding to a 3D direction. In this case, the roll parameter can correspond to the c value in the two-dimensional (2D) line, such as z=cy, which is obtained by projecting the corresponding 3D line to the zy plane. The pitch parameter can correspond to the b value in the 2D line, such as z=bx, which is obtained by projecting the corresponding 3D line to the xz plane. The yaw parameter can correspond to the a value in the 2D line, such as y=ax, which is obtained by projecting the corresponding 3D line to the xy plane.

[0065] In the following, the roll parameter, pitch parameter and yaw parameter will be represented by θ and ψ represent yaw. In addition, yaw can also be called heading.

[0066] Figure 3 : is a diagram showing an example of the operation of the navigation device. Figure 3 In operation 310, the navigation device determines the GPS validity. Based on the result of operation 310, it can be determined whether valid GPS data is obtained.

[0067] The situation where valid GPS data is obtained may include the situation where GPS data is received and the received GPS data is valid. The situation where valid GPS data is not obtained may include the situation where GPS data is received and the received GPS data is invalid, or the situation where no GPS data is received. GPS data may be received periodically based on a preset receiving cycle (e.g., 1 second). The situation where GPS data is not received may include the situation where GPS data is not received due to a communication failure when the receiving cycle passes, and the situation where GPS data is not received between receiving cycles. For example, in a situation where the frame rate of the AR image exceeds 1 frame per second (fps), the situation where GPS data is not received between receiving cycles may be a situation where other data needs to be used to replace the GPS data between GPS receiving cycles.

[0068] The navigation device may determine the validity of the GPS data by comparing a GPS-based speed and a GPS-based yaw rate with a sensor-based speed and a sensor-based yaw rate, respectively. The GPS-based speed and the GPS-based yaw rate are speed and yaw rate, respectively, measured using the GPS data. The sensor-based speed and the sensor-based yaw rate are speed and yaw rate, respectively, measured using sensors (e.g., a speed sensor and a steering sensor).

[0069] For example, the navigation device may obtain GPS data at a current point in time corresponding to the current position of the target device, and determine a GPS-based speed and a GPS-based yaw rate based on the GPS data obtained at the current point in time. In addition, the precise navigation device may obtain a sensor-based speed measured by a speed sensor of the target device, and a sensor-based yaw rate measured by a steering sensor of the target device. The navigation device may then determine the validity of the GPS data based on the results of comparing the GPS-based speed and the sensor-based speed, and comparing the GPS-based yaw rate and the sensor-based yaw rate. When the difference between the GPS-based speed and the sensor-based speed, and the difference between the GPS-based yaw rate and the sensor-based yaw rate are both less than their respective thresholds, the navigation device may determine that the GPS data is valid. Hereinafter, reference will be made to Figure 4 An example of determining the validity of GPS data is described in detail.

[0070] Figure 4 is a diagram showing an example of determining the validity of GPS data. The navigation device may determine the validity of GPS data by referring to highly robust sensors such as a speed sensor and a steering sensor. Figure 4 In operation 410, the navigation device may locate the location P corresponding to the GPS data at the current time point. GPS，t To determine the GPS-based speed VGPS and GPS-based yaw ψ GPS For example, the GPS-based velocity V can be determined as shown in Equations 1 and 2 GPS and GPS-based yaw ψ GPS .

[0071] [Equation 1]

[0072]

[0073] [Equation 2]

[0074]

[0075] In Equation 1, P GPS，t-1 Is the position corresponding to the GPS data at the previous time point t-1. Δt is the difference between the current time point t and the previous time point t-1, and corresponds to the processing cycle of the navigation device. For example, the navigation device can generate navigation parameters every Δt.

[0076] In this example, the GPS data may include information associated with the horizontal, vertical, and altitude directions, and thus the position corresponding to the GPS data may be a 3D position. In Equation 2, V GPS，lon is the GPS-based speed in the longitudinal direction, and V GPS，lat is the GPS-based velocity in the lateral direction. Therefore, the velocity V GPS，lon and V GPS，lat Can correspond to the speed V GPS longitudinal and transverse components.

[0077] In operation 420, the navigation device may determine the speed difference diff vel and angle difference ang The velocity difference diff can be determined as shown in Equations 3 and 4 vel and angle difference ang .

[0078] [Equation 3]

[0079] diff vel =|||V ＧPS ||-V car |

[0080] [Equation 4]

[0081]

[0082] In Equation 3, ||V GPS || is V GPS The amplitude, and V caris the speed of the target device measured by the speed sensor of the target device. In Equation 4, is the GPS-based yaw rate, and The GPS-based yaw rate may be determined based on the GPS-based yaw at a previous time point and the GPS-based yaw at a current time point. The sensor-based yaw rate may be measured by a steering sensor of the target device.

[0083] In operation 430, the navigation device may calculate the speed difference diff vel and angle difference ang With their respective thresholds thres v and thres a Make a comparison.

[0084] When the speed difference vel Less than the threshold thres v And the angle difference ang Less than the threshold thres a When the speed difference is , the navigation device can determine that the GPS data at the current time point is valid. vel Greater than the threshold thres v and / or angle difference ang Greater than the threshold thres a When the navigation device determines that the GPS data at the current time point is not valid.

[0085] Return to reference Figure 3 , in operation 320, the navigation device may determine the posture parameters. For example, the navigation device obtains valid GPS data at the current time point corresponding to the current position of the target device, and determines a first adjacent map element corresponding to the first area indicated by the valid GPS data at the current time point from a plurality of map elements of the map data. For example, the fact that the first adjacent map element corresponds to the first area may also indicate that the first adjacent map element is included in the first area. The first area may be an area within a range of, for example, 10 meters (m) from the position indicated by the valid GPS data at the current time point. Subsequently, the navigation device may determine the posture parameters of the target device at the current time point based on the first direction indicated by at least a portion of the first adjacent map element.

[0086] As described above, the map data may be based on an HD map. The HD map may include various map elements, including, for example, lanes, centerlines, and traffic signs and markings. The map elements in the HD map may be represented by a point cloud, and each point of the point cloud may correspond to a 3D location.

[0087] The navigation device may perform line fitting on a plurality of points included in the first-neighboring map element and identify a direction for each of the first-neighboring map elements. As described above, each point may correspond to a 3D position, and thus the direction for each of the first-neighboring map elements may also correspond to a 3D direction. The navigation device may identify the first direction based on the result of the line fitting.

[0088] The navigation device can identify the first direction by selecting at least a portion of the first adjacent map elements from the first adjacent map elements. Through such selection, map elements that are closely and actually associated with the target device can be selected as adjacent map elements. For example, when a vehicle passes through an intersection, map elements that are irrelevant to the vehicle's driving direction (e.g., lanes in a clockwise or right-turn direction) may be selected as adjacent map elements. Such adjacent map elements may be irrelevant to the vehicle's actual driving direction and may therefore produce an error effect in indicating the vehicle's posture. Therefore, through the above selection, such error elements can be eliminated and the accuracy of the posture parameters can be improved.

[0089] For example, the navigation device may determine GPS-based yaw based on valid GPS data at a current point in time and the position of the target device at a previous point in time. In this example, the position of the target device at the previous point in time may be based on valid GPS data at the previous point in time. However, if valid GPS data does not exist at the previous point in time, the position of the target device at the previous point in time may be calculated by applying dead reckoning (DR) to valid GPS data at another previous point in time.

[0090] The navigation device may then compare the map-based yaw corresponding to each of the first adjacent map elements with the determined GPS-based yaw and extract samples from the first adjacent map elements. As described above, as a result of performing line fitting on the first adjacent map elements, a 3D direction corresponding to each of the first adjacent map elements may be determined. Additionally, as described above with reference to Figure 2 The map-based yaw corresponding to each of the first-neighboring map elements may be determined by projecting a line corresponding to the 3D direction onto the xy plane. The navigation device may then extract as a sample the first-neighboring map element corresponding to the map-based yaw whose difference from the GPS-based yaw is less than a threshold.

[0091] In addition, the navigation device can identify the first direction by applying a random sampling consensus (RANSAC) algorithm to the samples extracted as described above. Through the RANSAC algorithm, samples with high similarity between samples can be averaged, and the direction corresponding to the result of the RANSAC algorithm can be identified as the first direction. Therefore, adjacent elements in the sample that hinder the posture estimation of the target device can be additionally eliminated, so that the first direction can be more likely to correspond to the actual posture of the target device.

[0092] The navigation device may determine a first map-based yaw parameter, a first map-based pitch parameter, and a first map-based roll parameter based on the first direction. The navigation device may determine each parameter by projecting a 3D line corresponding to the first direction onto each 2D plane, as described above with reference to Figure 2 Alternatively, the navigation device may determine each parameter by performing line fitting on each 2D plane on points included in the first adjacent map element corresponding to the first direction.

[0093] Additionally, the navigation device may determine the attitude parameter by verifying a first map-based yaw parameter, a first map-based pitch parameter, and a first map-based roll parameter. For example, the navigation device may determine the attitude parameter by comparing the sensor-based yaw at the current time point with the first map-based yaw corresponding to the first direction. In this example, the sensor-based yaw at the current time point may be calculated by applying the yaw rate measured by the steering sensor of the target device to the yaw of the target device at the previous time point.

[0094] When the difference between the sensor-based yaw and the first map-based yaw is less than a threshold, the navigation device may determine that the attitude parameter corresponds to the first direction. That is, the navigation device may determine the first map-based yaw parameter, the first map-based pitch parameter, and the first map-based roll parameter as the attitude parameters. When the difference between the sensor-based yaw and the first map-based yaw is greater than a threshold, the navigation device may determine the separately determined sensor-based yaw parameter, the second map-based pitch parameter, and the second map-based yaw parameter as the attitude parameters. When valid GPS data is not available, the sensor-based yaw parameter, the second map-based pitch parameter, and the second map-based roll parameter may be used. The sensor-based yaw parameter, the second map-based pitch parameter, and the second map-based roll parameter will be described in more detail below.

[0095] When valid GPS data is not available at the current time, the navigation device may obtain a sensor-based position at the current time corresponding to the current location of the target device. The sensor-based position at the current time may be calculated by applying the DR to the previous location of the target device. For example, the navigation device may calculate the sensor-based position at the current time by applying the DR based on speed data and steering data to the previous location of the target device.

[0096] The navigation device may then determine, from the plurality of map elements in the map data, a second adjacent map element corresponding to a second area indicated by the sensor-based position at the current time point, and determine a posture parameter of the target device at the current time point based on a second direction indicated by at least a portion of the second adjacent map element. The navigation device may identify the second direction by performing line fitting on a plurality of points included in the second adjacent map element.

[0097] However, when valid GPS data is not obtained, the GPS-based yaw may not be calculated, so RANSAC may be performed without additional sampling. For example, the navigation device may identify a second direction by applying the RANSAC algorithm to a second adjacent map element. Subsequently, the navigation device may determine a second map-based pitch parameter and a second map-based roll parameter based on the second direction. In this example, the yaw parameters may be calculated separately based on DR. For example, the navigation device may determine a sensor-based yaw parameter by applying the yaw rate measured by a steering sensor of the target device to the yaw of the target device at a previous point in time. The navigation device may then determine the sensor-based yaw parameter, the map-based second pitch parameter, and the map-based second roll parameter as attitude parameters.

[0098] Figure 5 : is a diagram showing an example of map data. Figure 5 The map data 520 includes various map elements, such as lanes, center lines, traffic signs and markings, etc. The map elements in the map data 520 can be represented by point clouds. A GPS-based position P can be specified for the map data 520 based on GPS data. GPS and may include GPS-based location P GPS The area including the first area 510 is set as the first area 510. The map element corresponding to the first area 510 can be selected as the first adjacent map element. However, when no valid GPS signal is received, a sensor-based location can be specified for the map data 520, and a second area including the sensor-based location can be set to determine the second adjacent map element.

[0099] Figure 6 is a diagram showing an example of determining posture parameters. Figure 6 , operations 611 to 615 described below may correspond to a case where valid GPS data is obtained, while operations 621 to 623 described below may correspond to a case where valid GPS is not obtained. Even in the case where valid GPS data is obtained, some of operations 621 to 623 may be performed to provide data required to perform operations 611 to 615.

[0100] In operation 611, the navigation device may determine the location P based on the GPS corresponding to the valid GPS data at the current time point. GPS，t and map data to determine the first adjacent map element map1 i In operation 612, the navigation device selects the first adjacent map element map1 i Determine Sample S. The navigation device may determine Sample S as expressed in Equation 5.

[0101] [Equation 5]

[0102]

[0103] In Equation 5, ψ map，i Is the first adjacent map element map1 i Each of ψ corresponds to a map-based yaw. GPS is the GPS-based yaw, and thres is the threshold. In addition, i is used to identify the first adjacent map element map1 i In this example, and with the GPS-based yaw ψ GPS The difference is less than the threshold map-based yaw ψ map，I Corresponding adjacent map elements map i can be determined as sample S.

[0104] In operation 613 , the navigation apparatus may determine a first map-based yaw parameter ψ by performing RANSAC on the sample S. map1，t , the first pitch parameter θ based on the map map1，t and the first roll parameter based on the map In the following, for the convenience of description, the determined first yaw parameter ψ based on the map is map1，t , the first pitch parameter θ based on the map mapl，t and the first roll parameter based on the map It is called the "first parameter group".

[0105] In operations 614 and 615, the navigation device may verify the first parameter set. For example, in operation 614, the navigation device calculates the yaw parameter ψ based on the sensor. car，t and the first map-based yaw parameter ψ map1，tThe angle difference between ang , and in operation 615 the angle difference diff ang and threshold thres a The sensor-based yaw ψ may be calculated in operation 623 car，t .

[0106] When the angle difference ang Less than the threshold thres a When the angle difference is ang Greater than the threshold thres a , the second parameter group can be determined as the posture parameters at the current time point. In this example, the second parameter group may include the sensor-based yaw parameter ψ car，t , the second pitch parameter θ based on the map map2，t and a second roll parameter based on the map A second map-based pitch parameter θ may be calculated in operation 622 map2，t and a second roll parameter based on the map

[0107] In operation 621, the navigation device may calculate the position P of the navigation device based on the sensor at the current time point. car，t and map data to determine the second adjacent map element map2 i The sensor-based position P can be calculated by applying the DR based on speed data and steering data to the previous position of the target device at the previous point in time. car，t In operation 622 , the navigation device may determine a second map-based pitch parameter θ by performing RANSAC on the second adjacent map element map12 . map2，t and a second roll parameter based on the map

[0108] In operation 623, the navigation device can adjust the yaw rate Δψ steer The yaw parameter ψ applied to the previous time point car，t-1 To determine the sensor-based yaw parameter ψ at the current time point car，t In this example, the yaw rate Aψ steer It can correspond to the change Δψ of the steering data during Δt steer , and can be measured by the steering sensor of the target device. When no valid GPS data is obtained, the sensor-based yaw parameter ψ car，t , the second pitch parameter θ based on the map map2，t and map-based roll parameters The second parameter group including is determined as the posture parameters at the current time input.

[0109] Return to reference Figure 3 , the navigation device determines the speed parameter. The navigation device may determine the speed parameter at the current time point using the posture parameter at the current time point determined in operation 320. For example, the navigation device may determine a direction cosine matrix (DCM) corresponding to the posture parameter at the current time point, and determine the speed parameter at the current time point by applying the DCM to a speed vector corresponding to the speed of the target device at the current time point, wherein the speed is measured by a speed sensor of the target device.

[0110] Figure 7 is a diagram showing an example of determining a speed parameter. Figure 7 In operation 710, the navigation device determines attitude parameters, including, for example, ψ t ,θ t and Operation 710 may correspond to the above reference Figure 3 In operation 720, the navigation device may calculate the t ,θ t and In operation 730, the navigation device may determine a speed parameter based on the speed data and the DCM. In operation 730, the following equation 6 may be used.

[0111] [Equation 6]

[0112]

[0113] In Equation 6, V N 、V E and V D are the speed in the north direction, the speed in the east direction and the speed in the downward direction respectively. In addition, V is the speed data, and is the DCM. Through Equation 6, the 3D velocity vector corresponding to the velocity parameter can be obtained.

[0114] Typically, GPS data may have relatively inaccurate altitude information, so it may not be easy to use the corresponding GPS information as the vehicle's 3D velocity. Furthermore, even if very accurate GPS data is received, it may not be easy to obtain the 3D velocity due to slight horizontal errors. However, according to example embodiments, a relatively accurate 3D velocity vector can be obtained using very accurate attitude parameters.

[0115] Return Reference Figure 3, the navigation device determines the position parameters in operation 340 and determines the lane change in operation 350. For example, the navigation device may determine the map-based lane by matching the valid GPS data at the current point in time with the map data, and determine the sensor-based lane by applying the lane change trigger factor to the sensor-based position of the target device at the current point in time. The sensor-based position of the target device at the current point in time may be calculated by applying the DR to the position of the target device at the previous point in time. The lane change trigger factor may be generated by comparing the position change of the target device in the lateral direction with the lane width, and the lane change trigger factor may have a value corresponding to the number of lanes changed. Subsequently, the navigation device may compare the map-based lane with the sensor-based lane and determine the position parameters of the target device at the current point in time.

[0116] Figure 8 is a diagram showing an example of determining position parameters. Figure 8 , operations 811, 812, and 813 may correspond to a situation where valid GPS data is obtained, while operations 821, 822, 823, and 824 may correspond to a situation where valid GPS data is not obtained. However, even if valid GPS data is obtained, some of operations 821 to 824 may be performed to provide data required to perform operations 811 to 813.

[0117] In operation 811, the navigation device may locate the GPS-based position P corresponding to the valid GPS data at the current time point based on the map data. GPS，t To perform map matching. As a result of map matching, a map-based position P can be generated map，t The navigation device can be the closest GPS-based location P GPS，t The center of the lane and the map-based position P map，t to match.

[0118] In operation 812, the navigation device can obtain the location P based on the map. map，t To detect lanes. In this operation, as a result of such lane detection, a map-based lane may be generated. map，t Through operation 812, the lane corresponding to the target device can be detected among various lanes on the road where the target device is located. In operation 813, the navigation device can map，t With sensor-based lanes car，t The lane based on the sensor can be determined by operation 823. car，t .

[0119] Responding to map-based lanes that correspond to each othermap，t and sensor-based lanes car，t , the map-based location P map，t is determined as a position parameter. In contrast, in response to map-based lanes that do not correspond to each other, map，t and sensor-based lanes car，t , the sensor-based position P car，t The lane change trigger factor Alane can be generated based on the sensor and can therefore be used to provide relatively accurate lane information. map，t Corresponding to the sensor-based lane lane based on the lane change trigger factor Alane car，t Only when the map-based location P car，t As a positional parameter.

[0120] In operation 821, the navigation device may determine a speed parameter V car，t Operation 821 may correspond to the above reference Figure 3 In operation 822, the navigation device may apply the DR to the sensor-based position P at the previous time point. car，t-1 , calculate the sensor-based position P at the current time point car，t Here, we can use the speed parameter V car，t The change Δψ during Δt steer To perform DR.

[0121] In operation 823 , the navigation device may apply the lane change trigger factor Δlane to the sensor-based position P car，t-1 To determine the lane based on the lane car，t In operation 824, the navigation device may generate a lane change trigger factor Δlane by determining the lane change. For example, the navigation device may generate the lane change trigger factor Δlane by comparing the position change of the target device in the lateral direction with the lane width. When valid GPS data is not obtained, the position P based on the sensor may be used to trigger the lane change. car，t Determined as a positional parameter.

[0122] Figure 9 is a diagram showing an example of determining a lane change. Figure 9 In operation 910, the navigation device may determine the posture parameter. Operation 910 may correspond to the above reference Figure 3 In operation 920, the navigation device may calculate the yaw parameter ψ based on the sensor. car，t and the map-based yaw parameter ψ map，t To calculate can correspond to the sensor-based yaw parameter ψ car，t and the map-based yaw parameter ψ map，t The difference between the map-based yaw parameter ψ map，t It can correspond to the first map-based yaw parameter ψ that is finally determined as the attitude parameter map1，t and the second map-based yaw parameter ψ map2，t Any one of .

[0123] In operation 930, the navigation device may Sensor-based speed V car and Δt to calculate the position change Δx in the longitudinal direction and the position change Δy in the transverse direction.

[0124] [Equation 7]

[0125]

[0126] In operation 940, the navigation device may generate a lane change trigger factor Alane by comparing the lateral position change Δy with the lane width. As the longitudinal distance of the target device accumulates, the lateral position change Ay may increase. Therefore, when the lateral position change Δy exceeds the lane width, a lane change trigger factor Δlane may be generated. The value of the lane change trigger factor Alane may correspond to the number of lanes being changed.

[0127] Figure 10 : is a flowchart showing an example of an operating method of a navigation device. Figure 10 In operation 1010, the navigation device may obtain valid GPS data at the current time point corresponding to the current position of the target device. In operation 1020, the navigation device may determine a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current time point from a plurality of map elements in the map data. In operation 1030, the navigation device may determine a posture parameter of the target device at the current time point based on a first direction specified by at least a portion of the first adjacent map element. The navigation device may also perform the above reference Figures 1 to 9 The operations described are as follows, and for the sake of brevity, more detailed and repeated descriptions will be omitted here.

[0128] Figure 11 : is a diagram showing an example of the configuration of a navigation device. Figure 11, the navigation device 1100 may include a processor 1110 and a memory 1120. The memory 1120 may be connected to the processor 1110 and configured to store instructions to be executed by the processor 1110, and data to be processed by the processor 1110 and / or data that has been processed by the processor 1110. The memory 1120 may include a non-transitory computer-readable storage medium, such as a high-speed random access memory (RAM) and / or a non-volatile computer-readable storage medium (e.g., at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device).

[0129] The processor 1110 can execute instructions to perform the above reference Figures 1 to 10 For example, the processor 1110 may obtain valid GPS data at a current time point corresponding to the current location of the target device, determine a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current time point from a plurality of map elements in the map data, and determine a posture parameter of the target device at the current time point based on a first direction indicated by at least a portion of the first adjacent map element. In addition, the navigation device 1100 may perform the above-mentioned operations with reference to Figures 1 to 10 Other operations and methods are described, and for the sake of brevity, more detailed and repeated descriptions of these operations and methods will be omitted here.

[0130] Figures 1 to 11The navigation devices 100 and 1100, processor 1110, memory 1120, other navigation devices, processors and memories, other devices, equipment, units, modules and other components of the operations described in the present application are implemented by hardware components configured to perform the operations performed by hardware components described in the present application. The examples of hardware components that can be used to perform the operations described in the present application include controllers, sensors, generators, drivers, memories, comparators, arithmetic logic units, adders, subtractors, multipliers, dividers, integrators and any other electronic components configured to perform the operations described in the present application where appropriate. In other examples, one or more hardware components for performing the operations described in the present application are implemented by computing hardware (e.g., by one or more processors or computers). Processors or computers can be implemented by one or more processing elements (e.g., logic gate arrays, controllers and arithmetic logic units, digital signal processors, microcomputers, programmable logic controllers, field programmable gate arrays, programmable logic arrays, microprocessors, or any other equipment or combination of equipment configured to respond in a defined manner and execute instructions to achieve desired results). In one example, a processor or computer includes or is connected to one or more memories storing instructions or software executed by the processor or computer. The hardware components implemented by the processor or computer can execute instructions or software, for example, an operating system (OS) and one or more software applications running on the OS to perform the operations described in this application. The hardware components can also access, manipulate, process, create and store data in response to the execution of instructions or software. For the sake of brevity, the singular terms "processor" or "computer" can be used in the description of the examples described in this application, but multiple processors or computers can be used in other examples, or the processor or computer can include multiple processing elements, or multiple types of processing elements, or both. For example, a single hardware component or two or more hardware components can be implemented by a single processor, or two or more processors, or a processor and a controller. One or more hardware components can be implemented by one or more processors, or a processor and a controller, and one or more other hardware components can be implemented by one or more other processors or another processor and another controller. One or more processors or a processor and a controller can implement a single hardware component or two or more hardware components. The hardware components may have any one or more of different processing configurations, examples of which include a single processor, independent processors, parallel processors, single instruction single data (SISD) multiprocessing, single instruction multiple data (SIMD) multiprocessing, multiple instruction single data (MISD) multiprocessing, and multiple instruction multiple data (MIMD) multiprocessing.

[0131] Perform the operations described in this application Figures 1 to 11The methods shown in the are performed by computing hardware, for example, by one or more processors or computers, wherein the computing hardware is implemented as described above to execute instructions or software to perform the operations performed by these methods described in this application. For example, a single operation or two or more operations can be performed by a single processor, or two or more processors, or a processor and a controller. One or more operations can be performed by one or more processors or a processor and a controller, and one or more other operations can be performed by one or more other processors or another processor and another controller. One or more processors or a processor and a controller can perform a single operation or two or more operations.

[0132] Instructions or software for controlling computing hardware (e.g., one or more processors or computers) to implement hardware components and perform methods as described above can be written as computer programs, code segments, instructions, or any combination thereof, for individually or collectively instructing or configuring one or more processors or computers to operate as machines or special-purpose computers to perform the operations performed by the above-mentioned hardware components and methods. In one example, the instructions or software include machine code directly executed by one or more processors or computers, such as machine code generated by a compiler. In another example, the instructions or software include more advanced code executed by one or more processors or computers using an interpreter. Instructions or software can be written in any programming language based on the block diagrams and flow charts shown in the accompanying drawings and the corresponding description in the specification (which discloses algorithms for performing the operations performed by the hardware components and the methods as described above).

[0133] The instructions or software for controlling computing hardware (e.g., one or more processors or computers) to implement hardware components and perform the methods described above, and any associated data, data files, and data structures, may be recorded, stored, or fixed in or on one or more non-transitory computer-readable storage media. Examples of non-transitory computer-readable storage media include read-only memory (ROM), random access memory (RAM), flash memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state disk, and any other device configured to store instructions or software and any associated data, data files, and data structures in a non-transitory manner and provide the instructions or software and any associated data, data files, and data structures to one or more processors or computers so that the one or more processors or computers can execute the instructions. In one example, the instructions or software and any associated data, data files, and data structures are distributed across a networked computer system so that one or more processors or computers store, access, and execute the instructions and software and any associated data, data files, and data structures in a distributed fashion.

[0134] Although this disclosure includes specific examples, it will be apparent after an understanding of the disclosure of this application that various changes in form and detail may be made to these examples without departing from the spirit and scope of the claims and their equivalents. The examples described herein should be considered merely descriptive and not for purposes of limitation. The description of features or aspects in each example is considered applicable to similar features or aspects in other examples. Suitable results may be achieved if the described techniques are performed in a different order and / or if components in the described systems, architectures, devices, or circuits are combined in a different manner and / or replaced or supplemented by other components or their equivalents. Accordingly, the scope of the disclosure is not limited by the detailed description, but by the claims and their equivalents, and all variations within the scope of the claims and their equivalents are interpreted as being included in this disclosure.

Claims

1. A method for operating a navigation device, the method comprising: Obtaining valid Global Positioning System (GPS) data at a current point in time corresponding to a current location of the target device; determining, from a plurality of map elements in the map data, a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current time point; as well as determining a posture parameter of the target device at the current time point based on a first direction specified by at least a portion of the first adjacent map element, Wherein, determining the posture parameter of the target device at the current time point based on the first direction includes: determining a GPS-based yaw based on the valid GPS data at the current time point and the location of the target device at a previous time point; and Samples are extracted from each of the first neighboring map elements by comparing a map-based yaw corresponding to each of the first neighboring map elements with the determined GPS-based yaw.

2. The operating method according to claim 1, wherein: The first direction is a three-dimensional 3D direction.

3. The operating method according to claim 1, wherein: The attitude parameters include a roll parameter, a pitch parameter and a yaw parameter.

4. The operating method according to claim 1, wherein: Determining the posture parameter of the target device at the current time point based on the first direction further includes: identifying the direction of each of the first adjacent map elements by performing line fitting on a plurality of points included in the first adjacent map elements and respectively corresponding to 3D positions.

5. The operating method according to claim 1, wherein: Determining the posture parameter of the target device at the current time point based on the first direction further includes: identifying the first direction by applying a random sampling consistent RANSAC algorithm to the extracted samples.

6. The operating method according to claim 1, wherein: Determining a posture parameter of the target device at the current time point based on the first direction includes: determining the posture parameter by comparing a sensor-based yaw at the current time point with a map-based yaw corresponding to the first direction, and The sensor-based yaw at the current time point is calculated by applying a yaw rate measured by a steering sensor of the target device to the yaw of the target device at a previous time point.

7. The operating method according to claim 6, wherein: In response to a difference between the sensor-based yaw and the map-based yaw being less than a threshold, it is determined that the pose parameter corresponds to the first direction.

8. The operating method according to claim 1, further comprising: Determine a direction cosine matrix DCM corresponding to the determined posture parameters of the target device at the current time point; as well as A velocity parameter of the target device at the current time point is determined by applying the DCM to a velocity vector corresponding to a velocity of the target device at the current time point, wherein the velocity is measured by a velocity sensor of the target device.

9. The operating method according to claim 1, further comprising: determining a map-based lane by matching the valid GPS data at the current time point with the map data; determining a sensor-based lane by applying a lane change trigger factor to a sensor-based position of the target device at the current point in time, wherein the sensor-based position is calculated by applying dead reckoning (DR) to a position of the target device at a previous point in time; as well as By comparing the lane based on the map and the lane based on the sensor, a position parameter of the target device at the current time point is determined.

10. The operating method according to claim 9, further comprising: The lane change trigger factor is generated by comparing a lane width with a position change of the target device in a lateral direction. The operating method according to claim 1 , further comprising determining whether the valid GPS data is obtained.

12. The operating method according to claim 11, wherein: Determining whether the valid GPS data is obtained includes: obtaining GPS data of the current time point corresponding to the current location of the target device; determining a GPS-based speed and a GPS-based yaw rate based on the obtained GPS data at the current time point; obtaining a sensor-based speed measured by a speed sensor of the target device and a sensor-based yaw rate measured by a steering sensor of the target device; and The validity of the GPS data is determined based on a result of comparing the GPS-based speed to the sensor-based speed and a result of comparing the GPS-based yaw rate to the sensor-based yaw rate. 13 . A non-transitory computer-readable storage medium storing instructions, wherein when the instructions are executed by a processor, the processor is caused to perform the operating method of claim 1 .

14. A method for operating a navigation device, the method comprising: In response to not obtaining valid global positioning system (GPS) data at a current point in time corresponding to a current location of the target device, obtaining a sensor-based location at the current point in time, wherein the sensor-based location at the current point in time is calculated by applying dead reckoning (DR) to a previous location of the target device and corresponds to the current location of the target device; determining, from a plurality of map elements, an adjacent map element corresponding to the area indicated by the sensor-based position at the current point in time; and determining a posture parameter of the target device at the current time point based on a direction specified by at least a portion of the adjacent map elements, Determining the posture parameter of the target device at the current time point based on the direction includes: Determining pitch and roll among the attitude parameters based on the direction; and The yaw in the attitude parameter is determined by applying a yaw rate measured by a steering sensor of the target device to the yaw of the target device at a previous point in time.

15. The operating method according to claim 14, wherein: Determining the posture parameter of the target device at the current time point based on the direction includes identifying the direction by performing line fitting on a plurality of points included in the adjacent map elements and respectively corresponding to 3D positions.

16. The operating method according to claim 14, wherein: Determining the posture parameter of the target device at the current time point based on the direction includes: identifying the direction by applying a random sampling consensus RANSAC algorithm to the adjacent map elements.

17. A navigation device comprising: The processor is configured to: Obtaining valid Global Positioning System (GPS) data at a current point in time corresponding to a current location of the target device; determining, from a plurality of map elements in the map data, a first adjacent map element corresponding to a first area indicated by the valid GPS data at the current time point; as well as determining a posture parameter of the target device at the current time point based on a first direction specified by at least a portion of the first adjacent map element, The processor is further configured to: determining a GPS-based yaw based on the valid GPS data at the current time point and a position of the target device at a previous time point; Samples are extracted from each of the first neighboring map elements by comparing a map-based yaw corresponding to the first neighboring map elements with the determined GPS-based yaw.

18. The navigation device according to claim 17, wherein: The processor is further configured to identify a direction of each of the first-neighboring map elements by performing line fitting on a plurality of points included in the first-neighboring map elements and respectively corresponding to three-dimensional (3D) positions.

19. The navigation device according to claim 17, wherein: The processor is further configured to: The first direction is identified by applying a random sampling consensus RANSAC algorithm to the extracted samples.

20. The navigation device according to claim 17, wherein: The processor is further configured to determine the attitude parameter by comparing the sensor-based yaw at the current time point with a map-based yaw corresponding to the first direction, and The sensor-based yaw at the current time point is calculated by applying a yaw rate measured by a steering sensor of the target device to the yaw of the target device at a previous time point.

21. The navigation device according to claim 20, wherein: In response to a difference between the sensor-based yaw and the map-based yaw being less than a threshold, it is determined that the pose parameter corresponds to the first direction.

22. The navigation device according to claim 17, wherein: The processor is further configured to: in response to not obtaining the valid GPS data at the current time point, obtaining a sensor-based position at the current time point, the sensor-based position at the current time point being calculated by applying dead reckoning (DR) to a previous position of the target device and corresponding to the current position of the target device; determining, from the plurality of map elements, a second adjacent map element corresponding to a second area indicated by the obtained sensor-based position at the current point in time; as well as A posture parameter of the target device at the current time point is determined based on a second direction specified by at least a portion of the second adjacent map element.

23. The navigation device according to claim 17, wherein: The processor is further configured to: Determine a direction cosine matrix DCM corresponding to the determined posture parameters of the target device at the current time point; as well as A velocity parameter of the target device at the current time point is determined by applying the DCM to a velocity vector corresponding to a velocity of the target device at the current time point, wherein the velocity is measured by a velocity sensor of the target device.

24. The navigation device according to claim 17, wherein: The processor is further configured to: determining a map-based lane by matching the valid GPS data at the current time point with the map data; determining a sensor-based lane by applying a lane change trigger factor to a sensor-based position of the target device at the current point in time, wherein the sensor-based position is calculated by applying dead reckoning (DR) to a position of the target device at a previous point in time; as well as By comparing the lane based on the map and the lane based on the sensor, a position parameter of the target device at the current time point is determined.

25. The navigation device according to claim 24, wherein: The processor is further configured to generate the lane change trigger factor by comparing a position change of the target device in a lateral direction with a lane width.

26. The navigation device according to claim 17, further comprising: Memory, which stores instructions, The processor is configured to execute the instructions to perform the following operations: obtain the valid global positioning system GPS data, determine the first adjacent map element, and determine the posture parameter.

Images