Own-position estimating device and own-position estimating method

Abstract

This own-position estimating device comprises: an own-position estimating unit that estimates the own-position of a vehicle on the basis of vehicle information measured by a vehicle-mounted sensor and observation information output by a receiver that receives positioning radio waves from a plurality of positioning satellites; a target satellite selecting unit that selects a target positioning satellite from among the plurality of positioning satellites on the basis of the azimuth angle and angle of elevation of the positioning satellites as seen from the vehicle, with a first direction as a reference axis, and the validity of positioning augmentation information of the positioning satellites; and a position updating unit that updates the position of the own-position estimated by the own-position estimating unit in at least the first direction on the basis of the pseudorange between the selected at least one target positioning satellite and the vehicle, and the positioning augmentation information.

Description

Self-location estimation device and self-location estimation method

[0001] The present disclosure relates to a self-location estimation device and a self-location estimation method that utilize a global navigation satellite system (GNSS).

[0002] In recent years, positioning methods that perform positioning based on radio waves received from positioning satellites have made it possible to perform highly accurate positioning by utilizing positioning augmentation information services provided by specific positioning satellites, such as the Centimeter Level Augmentation Service (CLAS) and the High Accuracy Service (HAS). These augmentation information services acquire state quantities for each factor contained in the augmentation information by receiving one frame of the augmentation information transmitted from the positioning satellite with a receiving antenna on a vehicle. The factors include satellite clock error, satellite orbit error, satellite signal bias error, and ionospheric delay error. For example, in the CLAS, one frame of the augmentation information transmitted from the Quasi-Zenith Satellite System (Michibiki) lasts 30 seconds.

[0003] The amount of error for each factor is used to correct the information obtained from the positioning radio waves received from each positioning satellite, thereby achieving highly accurate positioning. Furthermore, Patent Document 1 discloses a technology for estimating unknown errors that are not distributed, thereby improving the accuracy of the vehicle's position.

[0004] However, one frame of positioning augmentation information must be received continuously. If an obstacle such as a footbridge, overpass, or tunnel exists between a specific positioning satellite transmitting the positioning augmentation information and the receiving antenna during frame reception, the reception of the positioning augmentation information is hindered, making the error amount for each factor contained in that frame unusable. Furthermore, even if reception of one frame is completed without any interruption, the error amount for each factor changes over time. For this reason, after a certain period of time has passed, the error amount for each factor contained in that frame becomes unusable. The time until this becomes unusable varies depending on the type of positioning augmentation information service and the expected positioning accuracy, but is often set to around 60 seconds.

[0005] Furthermore, a technique has been known that combines satellite positioning results with inertial measurement units (IMUs) such as acceleration sensors and gyro sensors mounted on a moving object, as well as external sensor devices such as wheel speed sensors, cameras, and LiDAR (Light Detection and Ranging). This technique can interpolate intermittent satellite positioning outputs and suppress sudden position deviations. Several GNSS and IMU fusion methods have been proposed, and using these GNSS and IMU fusion methods not only interpolates intermittent satellite positioning outputs, but also enables position calculation using autonomous navigation when GNSS positioning is unavailable.

[0006] Furthermore, the output of a gyro sensor used in autonomous navigation generally tends to change depending on the ambient temperature, and position errors tend to accumulate during long periods of autonomous navigation. Patent Document 2 discloses a technology that uses an estimated position based on autonomous navigation when positioning radio waves are blocked, or that determines that the positioning radio waves have changed from a blocked state to a received state, and corrects the accumulated error in the estimated position based on the absolute position determined by GPS.

[0007] International Publication No. 2017 / 154779 JP 10-221099 Publication

[0008] However, in the above-described conventional technology, in order to estimate unknown errors or determine that positioning radio waves have been received after being blocked, and to calculate absolute position, it is necessary to observe the positioning radio waves of at least four or more positioning satellites and perform GNSS positioning. Positioning satellites from which positioning radio waves can be directly received as viewed from the vehicle are also called "visible satellites." For example, near tunnel entrances or in urban areas where the number of visible satellites is likely to change, the timing at which the necessary positioning satellites become visible varies. In such cases, the vehicle must wait until the satellite positioning environment stabilizes, which takes time before GNSS positioning can be performed. As a result, there is a problem in that erroneous positioning results are continuously output until the satellite positioning environment stabilizes.

[0009] Given the above situation, there was a demand for a method to quickly eliminate accumulated position errors using autonomous navigation at a point where the state in which the number of visible satellites is prone to change has been resolved, without having to wait until the satellite positioning environment stabilizes.

[0010] In order to solve the above problem, a self-position estimation device of one embodiment of the present invention comprises a self-position estimation unit that estimates the vehicle's self-position based on vehicle information measured by a sensor mounted on the vehicle and observation information output by a receiver that receives positioning radio waves from multiple positioning satellites; a target satellite selection unit that selects a target positioning satellite from the multiple positioning satellites based on the azimuth angle and elevation angle of the positioning satellite as seen from the vehicle with a first direction as a reference axis, and the validity of the positioning augmentation information of the positioning satellite; and a position update unit that updates at least the first direction position of the self-position estimated by the self-position estimation unit based on the pseudorange and positioning augmentation information between the vehicle and at least one target positioning satellite selected by the target satellite selection unit.

[0011] According to at least one aspect of the present invention, at a point where the state in which the number of visible satellites is likely to change is lifted, it is possible to quickly eliminate accumulated position errors through autonomous navigation without waiting until the satellite positioning environment stabilizes. Problems, configurations, and effects other than those described above will become apparent from the following description of the preferred embodiment of the present invention.

[0012] FIG. 1 is a block diagram showing an example of the configuration of a self-location estimation system including a self-location estimation device according to a first embodiment of the present invention. FIG. 2 is a block diagram showing an example of the hardware configuration of a computer included in the self-location estimation device according to the first embodiment of the present invention. FIG. 3 is a flowchart showing an example of the flow of processing by a self-location estimation unit of the self-location estimation device according to the first embodiment of the present invention. FIG. 4 is a flowchart showing an example of the flow of processing by a target satellite selection unit of the self-location estimation device according to the first embodiment of the present invention. FIG. 5 is a flowchart showing an example of the flow of processing by a position update unit of the self-location estimation device according to the first embodiment of the present invention. FIG. 6 is a diagram schematically showing an operation of the self-location estimation device according to the first embodiment of the present invention. FIG. 7 is a block diagram showing an example of the configuration of a self-location estimation system including a self-location estimation device according to a second embodiment of the present invention. FIG. 8 is a block diagram showing an example of the configuration of a self-location estimation system including a self-location estimation device according to a third embodiment of the present invention. FIG. 9 is a block diagram showing an example of the configuration of a self-location estimation system including a self-location estimation device according to a fourth embodiment of the present invention.

[0013] Hereinafter, examples of modes for carrying out the present invention (hereinafter referred to as "embodiments") will be described with reference to the accompanying drawings. In this specification and the accompanying drawings, identical or similar components are given the same reference numerals, and redundant explanations may be omitted or only differences may be explained. The number of each component may be singular or plural unless otherwise specified.

[0014] First Embodiment First, a self-location estimation device according to a first embodiment of the present invention will be described with reference to FIG.

[0015] 1 is a block diagram showing an example of the configuration of a self-location estimation system including a self-location estimation device according to a first embodiment of the present invention. As shown in the figure, a self-location estimation device 1 according to this embodiment is connected to a sensor 2 and a GNSS receiver 3 to configure a self-location estimation system 10. The self-location estimation device 1 includes processing units: a self-location estimation unit 11, a target satellite selection unit 12, and a position update unit 13. The self-location estimation device 1 can be configured using an ECU (Electronic Control Unit), for example.

[0016] The self-position estimation unit 11 estimates the vehicle's own position based on vehicle information measured by a sensor 2 mounted on the vehicle and observation information output by a GNSS receiver 3 that receives positioning radio waves from multiple positioning satellites (hereinafter sometimes abbreviated as "satellites"). The target satellite selection unit 12 selects a target positioning satellite from the multiple positioning satellites based on the azimuth angle and elevation angle of the positioning satellite as seen from the vehicle with the first direction as a reference axis, and the validity of the positioning augmentation information of the positioning satellite. The position update unit 13 updates the position of the self-position estimated by the self-position estimation unit 11 in at least the first direction, based on the pseudorange between the vehicle and at least one target positioning satellite selected by the target satellite selection unit 12 and the positioning augmentation information. Details of the self-position estimation unit 11, the target satellite selection unit 12, and the position update unit 13 will be described later.

[0017] The sensor 2 mounted on the vehicle outputs at least one of a sensor output representing the amount of wheel rotation, a sensor output representing the direction of the wheels, and a motion sensor output observing vehicle motion. Specifically, the sensor output representing the amount of wheel rotation refers to, for example, a wheel speed pulse obtained from a rotary encoder attached to a drive shaft or a brake drum, or, in the case of an EV, a signal obtained from a resolver in a driving motor. The sensor output representing the direction of the wheels refers to, for example, a steering wheel angle output obtained from a rotary encoder attached to a steering shaft, or a steering angle output observing the steering angle of a tire driven in conjunction with the steering wheel angle. The motion sensor output observing vehicle motion refers to, for example, an output representing the acceleration, angular velocity, angular acceleration, etc. of the vehicle observed by a gyro sensor or acceleration sensor mounted on the vehicle body.

[0018] The GNSS receiver 3 includes an antenna for receiving radio waves transmitted from one or more GNSS satellites that transmit positioning signals (e.g., one or more of an L1 signal, an L2 signal, an L5 signal, etc.) and radio waves transmitted from positioning satellites that transmit positioning augmentation signals. Examples of GNSS satellites that transmit positioning signals include GPS satellites, Galileo satellites, GLONASS satellites, BeiDou satellites, and QZSS (registered trademark) satellites. The positioning augmentation signals include correction information for, for example, satellite clock error, satellite orbit error, ionospheric propagation delay, and tropospheric propagation delay. Examples of positioning satellites that transmit positioning augmentation signals include MTSAT, SBAS satellites, QZSS satellites, and Galileo satellites.

[0019] The GNSS receiver 3 also acquires raw data required to calculate the position of the vehicle from the positioning signals transmitted by each GNSS satellite, calculates the position, speed, direction, etc. of the vehicle from the raw data, and outputs one or more of the raw data, the positioning result, and the positioning augmentation signal to the self-position estimation device 1. The raw data includes information such as the pseudo-distance to the vehicle, Doppler shift (amount of change in carrier frequency), navigation message, GNSS-Time, etc. The positioning result includes, for example, the position, speed, direction, positioning time, satellites used for positioning, etc. of the vehicle.

[0020] The self-position estimation unit 11 outputs a self-position estimated based on a sensor output representing the amount of wheel rotation, a sensor output representing the direction of the wheels, a motion sensor output observing vehicle motion, and observation information from GNSS satellites. For example, if the GNSS receiver 3 can observe and track a sufficiently large number of positioning satellites (e.g., 20 or more), the satellite configuration is good (e.g., an HDOP (Horizontal Dilution Of Precision) value of 0.7 or less), and the pseudorange residual of each positioning satellite is sufficiently small (e.g., 1 m or less), the error in the positioning position determined by the GNSS receiver 3 is considered small, and the positioning result is output as is as the self-position. The DOP value is a numerical value representing the degree of degradation of positioning accuracy, and the HDOP value (Horizontal Dilution Of Precision) is one example.

[0021] Alternatively, for example, if the GNSS receiver 3 can observe a certain number of positioning satellites (for example, about 10 to 15 satellites), the satellite configuration is good (for example, the HDOP value is 0.7 or less), and the pseudorange residual of each positioning satellite is not sufficiently small (for example, there are multiple positioning satellites with residuals of 10 m or more), the self-position estimation unit 11 takes a weighted average of the position measured by the GNSS receiver 3 and an estimated position estimated by the dead reckoning method (autonomous navigation) from the self-position output last time, and outputs this as the self-position. Note that the weight of the weighted average at this time can be determined based on the number of positioning satellites, the HDOP value, the pseudorange residual, etc.

[0022] There are several well-known techniques for the dead reckoning method. For example, it is possible to calculate the vehicle position using the Ackermann model based on the wheel rotation amount and wheel direction (steering angle). Alternatively, instead of the dead reckoning method, the estimated position may be estimated by integrating the output of a motion sensor that observes the vehicle motion and calculating the relative movement amount from the vehicle's past position.

[0023] The self-position estimation unit 11 also has the function of judging the reception status based on the positioning results from the GNSS satellites and determining whether the positioning radio waves have been interrupted or have returned to normal. The self-position estimation unit 11 determines that the positioning radio waves have been interrupted when the strength of the positioning radio waves received by the GNSS receiver 3 is below a predetermined value. Because the strength of the received positioning radio waves does not become zero due to diffuse reflection from structures, the diffusely reflected positioning radio waves can be excluded by setting a radio wave strength threshold. Alternatively, if the GNSS receiver 3 has an internal function for determining whether the positioning radio waves have been interrupted, the self-position estimation unit 11 may use the interruption determination result (and information on the radio wave strength of the positioning radio waves) as is.

[0024] The target satellite selector 12 selects as target positioning satellites those whose azimuth and elevation angles as seen from the vehicle with respect to the first direction as a reference axis are equal to or less than thresholds and whose positioning augmentation information is valid. Here, the first direction refers to a direction parallel to the road surface and perpendicular to the vehicle's direction of travel, i.e., a direction to the side of the vehicle, with no particular distinction made between left and right. The received positioning augmentation information is valid for a certain period of time; for example, in the case of the CLAS system, the validity period is 60 seconds.

[0025] If there are positioning satellites with valid positioning augmentation information within a specified azimuth angle range (e.g., within ±30 degrees) and a specified elevation angle range (e.g., 0 to 30 degrees) from this first direction, one or more of the positioning satellites are selected, and information that can identify the selected positioning satellite, such as the type and ID of the selected positioning satellite, is output, as well as the raw data of the positioning satellite.

[0026] However, the reference axis is not limited to the first direction, i.e., the side of the vehicle, and can be set arbitrarily because it is used as a reference for converting the azimuth angle and elevation angle of the positioning satellite as viewed from the vehicle into numerical values.

[0027] The position update unit 13 updates the vehicle position based on the estimated position obtained from the self-position estimation unit 11, the disruption determination result, and information from the selected positioning satellite obtained from the target satellite selection unit 12. In this process, the position update unit 13 calculates a position corrected for an error equivalent to a gyro drift error when the disruption state is released after the disruption state has continued for a certain period of time. The certain period is at least the time required for the gyro drift error to become large to a certain extent (for example, to a level that cannot be ignored from the perspective of positioning accuracy), and is within a range in which correction can be performed within the validity period of the positioning augmentation information, such as several tens of seconds (for example, 10 to 50 seconds).

[0028] Then, the position update unit 13 uses the error-corrected position to laterally correct its own position relative to the route obtained by the dead reckoning method or the like, outputs the corrected position information, and updates the past own position of the self-position estimation unit 11. A detailed processing flowchart will be described later. Furthermore, at times other than the aforementioned (when the uninterrupted state continues or the interrupted state continues), the position update unit 13 outputs the output of the self-position estimation unit 11 as is.

[0029] [Hardware Configuration of Computer] Here, the hardware configuration of the computer included in the self-location estimation device 1 will be described with reference to FIG.

[0030] Fig. 2 is a block diagram showing an example of the hardware configuration of a computer included in the self-location estimation device 1. The illustrated computer 20 is an example of hardware used as a computer. In the self-location estimation device 1 shown in Fig. 1, the computer 20 (computer) executes a program to realize the functions of each processing unit. This realizes a self-location estimation method in which each processing unit works in cooperation with each other. The computer 20 can be configured using one or more microcontrollers.

[0031] The computer 20 includes a CPU (Central Processing Unit) 21, a ROM (Read Only Memory) 22, and a RAM (Random Access Memory) 23, all connected to a system bus. The computer 20 further includes a non-volatile storage 24, a timer 25, an input / output interface 26, and a network interface 27.

[0032] The CPU 21 reads out the program code of the software that realizes each function according to this embodiment from the ROM 22, loads it into the RAM 23, and executes it. Variables, parameters, etc. that are generated during the calculation processing of the CPU 21 are temporarily written to the RAM 23, and these variables, parameters, etc. are read out as appropriate by the CPU 21. The function of each processing unit is realized by the CPU 21 executing the program code read out from the ROM 22. However, other processors such as an MPU (Micro Processing Unit) may be used instead of the CPU 21.

[0033] The nonvolatile storage 24 is an example of a recording medium, and is capable of storing data used by programs, data obtained by executing programs, etc. The nonvolatile storage 24 may also store an operating system (OS) or programs executed by the CPU 21. The nonvolatile storage 24 may be a hard disk drive (HDD), a solid state drive (SSD), an optical or magnetic disk medium, a semiconductor memory card, or the like.

[0034] The timer 25 is a timekeeping unit that measures time. For example, the timer 25 can calculate the elapsed time by counting the number of clock signals that the CPU 21 periodically outputs.

[0035] The input / output interface 26 is an input / output device that can communicate with the sensors 2 and the GNSS receiver 3 provided in the vehicle.

[0036] The network interface 27 may be a communication device such as a network interface card (NIC). The network interface 27 may transmit and receive various data to and from an external device via a communication network such as a CAN or a dedicated line connected to a terminal of the NIC. The external device may be, for example, another ECU mounted on the vehicle, a server capable of communicating via a wide area communication network, or a communication device capable of communicating via OTA (Over The Air). The functions of the network interface 27 and the input / output interface 26 may be configured as a single communication device.

[0037] 3 to 5 are flowcharts showing an example of the flow of processing by the self-position estimation device 1 of Fig. 1. The contents of the processing will be explained below with reference to these figures.

[0038] [Processing by Self-Location Estimation Unit] Fig. 3 is a flowchart showing an example of the flow of processing by the self-location estimation unit 11 of the self-location estimation device 1. When the self-location estimation unit 11 starts the self-location estimation processing shown in Fig. 3, first, in process S1, it acquires sensor information and observation information of GNSS satellites.

[0039] Next, in process S2, the self-position estimation unit 11 determines whether the error in the GNSS-measured position is sufficiently small. The self-position estimation unit 11 checks whether the following logical product conditions are met: the number of tracking positioning satellites is equal to or greater than a predetermined threshold (e.g., 20 satellites), the HDOP value indicating the satellite arrangement is equal to or less than a predetermined threshold (e.g., 0.7), and the maximum value of the pseudorange residual of the satellites used for positioning relative to the positioning result coordinates is equal to or less than a predetermined threshold (e.g., 1 m). If the logical product conditions are met, the self-position estimation unit 11 determines that the error in the GNSS-measured position is sufficiently small (YES branch); if not, it determines that the error is not sufficiently small (NO branch).

[0040] If the result of step S2 is YES, then in step S5 the self-position estimation unit 11 sets the GNSS positioning result as the self-position. On the other hand, if the result of step S2 is NO, then in step S3 the self-position estimation unit 11 calculates a weight for calculating a weighted average of the position measured by the GNSS receiver 3 and the estimated position estimated by the dead reckoning method from the self-position output last time.

[0041] In this process S3, the self-position estimation unit 11 calculates a weight from the number of positioning satellites being tracked, the HDOP value, the maximum value of the pseudorange residual, and the short-term fluctuation of the sensor output. An example of this calculation is shown below. Let N be the number of positioning satellites being tracked, D be the HDOP value, and R be the maximum value of the pseudorange residual. In this case, if the coefficient of the positioning position determined by the GNSS receiver 3 is CG, then the calculation can be performed as shown in the following equation (1).

[0042] Here, F １ (x) to F ３ (x) is a function, and has the following content: Thr1 to Thr6 are thresholds for the parameter x(N, D, R).

[0043] 0x <Thr1 F1(x)=(x-Thr1) / (Thr2―Thr1) Thr1≦x<Thr2 1 Thr2≦x

[0044] 1 x <Thr3 F2(x)=(x-Thr3) / (Thr4―Thr3) Thr3≦x<Thr4 0 Thr4≦x

[0045] 1 x <Thr5 F3(x)=(x-Thr5) / (Thr6―Thr5) Thr5≦x<Thr6 0 Thr6≦x

[0046] That is, if each parameter is better than the corresponding threshold, the CG takes the maximum value of 1, and if the positioning conditions are not good from each viewpoint, the CG gradually decreases.

[0047] Furthermore, if the sensor output after the previous processing S3 is defined as S(i) and the coefficient of the estimated position estimated by the dead reckoning method from the previously output self-position is defined as CD, then the calculation can be performed as shown in the following equation (2).

[0048] Here, F ４ (x) is a function with the following contents: Thr7 is a threshold for VAR(x). VAR(x) represents the variance of the sensor output.

[0049] 1 VAR(x) <Thr7 F4(x)=Thr7 / VAR(S) Thr7≦VAR(x)

[0050] That is, when the variance of the sensor output is small and the vehicle is moving smoothly, CD takes the maximum value of 1, and when this is not the case, CD gradually decreases.

[0051] In step S3, the weights of the weighted average, CG and CD, calculated in this way are output, and the process proceeds to step S4. Note that the calculation of CG and CD described above is just an example, and other calculation formulas may be used, including setting the weight of one of CG and CD to 0 and the other to 1.

[0052] Next, in process S4, the self-position estimation unit 11 calculates a weighted average of the position measured by the GNSS receiver 3 and the estimated position estimated by the dead reckoning method from the previously output self-position based on the weight of the weighted average calculated in process S3, and sets the weight as the self-position. Note that the weight used for this weighted average may be the most recent value calculated in process S3, but is not limited to this. For example, taking into account gradual changes in the positioning environment, weights calculated using a time-series smoothing process (e.g., a Kalman filter or a moving average) may be used. This has the effect of reducing the adverse effects of sudden noise and obtaining a stable self-position (output position).

[0053] Furthermore, the output position Pout = (CG PGNSS + CD PDR) / (CG + CD) may be calculated from a weighted average of the GNSS positioning position "PGNSS" and the position "PDR" obtained by the dead reckoning method, by directly using the latest value or a weight calculated using a time-series smoothing process. Alternatively, the output position Pout may be calculated as follows, for example, by using an appropriate function FS(x) for adjusting the sensitivity: Pout = (FS(CG) PGNSS + FS(CD) PDR) / (FS(CG) + FS(CD)).

[0054] When processing S4 or S5 is completed, the self-position estimation unit 11 proceeds to processing S6, in which the weight and the self-position are stored in memory (for example, RAM 23 in FIG. 2). In processing S6, the self-position estimation unit 11 stores at least the weight of the weighted average for a certain period of time or a certain number of processing times, the self-position, the traveled distance, and the traveled speed for use in the position update unit 13 described below. Here, the traveled distance refers to the amount of vehicle movement calculated by taking into account the wheel radius in addition to sensor information such as the amount of wheel rotation. The traveled speed refers to information combining the average vehicle speed for a certain period of time or a certain number of processing times with the movement direction vector.

[0055] In process S2, if the error in the GNSS-measured position is sufficiently small (YES branch), the weights for the weighted average are set as CG=1 and CD=0, and weights equivalent to using only the position measured by the GNSS receiver 3 are stored. This can be implemented as a ring buffer, for example. The self-position estimation unit 11 outputs the self-position according to the set weights to the position update unit 13, and ends the series of processes (proceed to END).

[0056] [Processing of the Target Satellite Selector] FIG. 4 is a flowchart showing an example of the processing flow by the target satellite selector 12 of the self-location estimation device 1. When the target satellite selector 12 starts the target satellite selection process shown in FIG. 4, it first acquires positioning augmentation information and GNSS satellite observation information in step S11. In step S11, the target satellite selector 12 decodes the content of the positioning augmentation information, which can be used to reduce errors due to satellite positioning, and acquires information for correcting satellite clock errors and satellite orbit errors. At this time, the target satellite selector 12 individually sets a timer representing the validity period of the positioning augmentation information for each positioning satellite to be corrected (i.e., augmented). The target satellite selector 12 then subtracts the timer representing the validity period as time passes, and determines that the positioning augmentation information is valid if the value (remaining time) is positive. Furthermore, the target satellite selector 12 determines that the positioning augmentation information has become invalid if the value becomes zero or less. This validity period may be set to a different value depending on the source of the positioning augmentation information, the positioning satellite system to be augmented, the type of error to be augmented, etc. Using a timer that individually indicates the validity period has the effect of making it possible to reliably distinguish between highly accurate positioning satellites.

[0057] For example, because the satellite clock error (satellite clock error) in the positioning augmentation information has a large impact on the positioning results, the validity period may be set to 5 seconds from the time the augmentation information is received. Alternatively, because the ionospheric error (ionospheric propagation delay) in the positioning augmentation information for each satellite changes relatively slowly, the validity period may be set to 30 seconds from the time the augmentation information is received. In this case, the positioning augmentation information is determined to be valid when the remaining times on all timers for that satellite are positive. Note that the ionospheric error for each satellite can be calculated from the satellite orbit information to calculate the elevation angle and azimuth angle of the satellite relative to the approximate position of the self-location estimation device 1, and then from information on the ionospheric error in that direction (region), the altitude of the ionosphere on the propagation path, and the angle of the passing radio waves relative to the ionosphere.

[0058] The target satellite selector 12 also determines whether each positioning satellite has been observed based on the observation information. For example, this determination may be made by determining that each positioning satellite has been observed if the radio wave strength of the positioning radio waves is stronger than a predetermined radio wave strength using the received C / NO (carrier-to-noise ratio) of each positioning satellite. Alternatively, the target satellite selector 12 may determine whether the received positioning radio waves are multipath or direct waves using an antenna capable of detecting the transmission direction of radio waves, and determine that the positioning satellite has been observed only if the received positioning radio waves are direct waves. If it is determined that each positioning satellite has not been observed, the value of the timer representing the valid time for that positioning satellite can be set to zero, which has the effect of preventing erroneous corrections resulting from uncertain positioning signals.

[0059] (Variations on Presence or Absence of Positioning Satellite Observation) Alternatively, the target satellite selection unit 12 may use sensors such as cameras or LiDAR (not shown) when determining whether each positioning satellite has been observed. In recent years, vehicle-mounted cameras and LiDAR have become less expensive, and multiple of these external sensors may be installed to observe the entire periphery of the vehicle. Many known technologies have been proposed that use cameras or LiDAR to recognize surrounding structures such as buildings and overpasses. Based on information about structures recognized using these known technologies and the position information of the positioning satellite contained in the positioning radio waves, it is possible to determine whether the direction of the positioning satellite is blocked by a structure. Using this, it may be determined that each positioning satellite has been observed if it is not blocked by a structure. This eliminates radio waves reflected by structures and the like from the received positioning radio waves, preventing a decrease in the accuracy of position correction.

[0060] Next, in process S12, the target satellite selection unit 12 determines whether there is a positioning satellite whose positioning augmentation information is still valid. In process S12, the target satellite selection unit 12 references the value of a timer representing the validity period set individually for each positioning satellite and determines whether the positioning augmentation information for each error of each positioning satellite is still valid (validity). If corresponding positioning augmentation information exists for a certain positioning satellite and no invalid positioning augmentation information exists, the target satellite selection unit 12 determines that the positioning satellite is a positioning satellite whose positioning augmentation information is still valid. That is, in process S12, positioning satellites that are not subject to augmentation are determined to be invalid (invalid), and positioning satellites that are subject to augmentation but whose validity period has expired are also determined to be invalid (invalid).

[0061] In this way, the validity of the positioning augmentation information for a positioning satellite is determined based on whether the positioning satellite is a target for augmentation by the positioning augmentation information and whether the validity period of the positioning augmentation information has expired.

[0062] On the other hand, it is not necessary for all positioning-related information to be augmented. For example, if the distributed positioning augmentation information does not include information on atmospheric errors, the validity or invalidity of the timer indicating the validity period of this information is not determined. The positioning augmentation information is required to include at least information indicating errors caused by individual positioning satellites (for example, satellite clock errors, satellite orbit errors).

[0063] If it is determined in process S12 that the positioning satellite has valid augmentation information (YES branch), information that can identify the positioning satellite and its location information such as azimuth and elevation angles are passed to subsequent process S13. On the other hand, if there is no positioning satellite with valid augmentation information in process S12 (NO branch), satellite selection is not performed (proceed to process S15).

[0064] In process S13, the target satellite selection unit 12 determines whether there is a positioning satellite whose azimuth angle and elevation angle from the vehicle satisfy predetermined conditions. In process S13, the target satellite selection unit 12 first acquires the position information of the positioning satellite contained in the positioning radio waves, and calculates the relative position of each positioning satellite to the vehicle taking into account the vehicle's position. That is, the target satellite selection unit 12 can calculate the azimuth angle, elevation angle, and distance of each positioning satellite based on the vehicle's position and the vehicle's direction of travel. Note that the vehicle's position and vehicle direction are affected by various errors, but generally correspond to the actual position and direction, so the estimation results calculated by the self-position estimation unit 11 are used.

[0065] Next, the target satellite selection unit 12 determines whether the azimuth angle, elevation angle, and distance of each positioning satellite satisfy predetermined conditions. The predetermined conditions are conditions for selecting a positioning satellite that is located in a favorable position relative to the vehicle when the vehicle has passed through a tunnel or a city with many buildings, and the condition in which the number of visible satellites is likely to change is resolved. If the target satellite selection unit 12 determines that there is one or more positioning satellites that satisfy the determination conditions (YES branch), it passes information that can identify the positioning satellite to the subsequent process S14 for selecting a positioning satellite. On the other hand, if the target satellite selection unit 12 determines that there is no positioning satellite that satisfies the determination result (NO branch), it does not select a satellite (proceeds to process S15).

[0066] In process S14, the target satellite selection unit 12 calculates an evaluation value for each positioning satellite based on conditions such as azimuth angle and elevation angle, and selects the positioning satellite with the highest evaluation value. In this process S14, the target satellite selection unit 12 calculates an evaluation value for each positioning satellite from, for example, the azimuth angle and elevation angle of the positioning satellite and their respective reference values, and selects the target positioning satellite based on the evaluation value. Note that when the target satellite selection unit 12 receives one piece of information that can identify a positioning satellite from process S13, it outputs to the position update unit 13 that the positioning satellite has been selected, and ends the process (proceeds to END).

[0067] Furthermore, when information capable of identifying multiple positioning satellites is passed from process S13, the target satellite selection unit 12 calculates the evaluation value of each positioning satellite using the reference value ThrPnt for the azimuth, the reference value ThrEle for the elevation angle, and the adjustment coefficient α for the azimuth angle and elevation angle, according to the following formula (3): Here, the evaluation value of positioning satellite N is EvaN, the azimuth angle is PntN, and the elevation angle is EleN.

[0068]

[0069] That is, when the azimuth angle and elevation angle are close to the respective reference values, the evaluation value becomes large. The target satellite selection unit 12 outputs to the position update unit 13 that the positioning satellite with the largest calculated evaluation value has been selected from among the multiple positioning satellites, and then ends the process (proceeds to END).

[0070] It is important that the selected positioning satellite is close to the direction perpendicular to the vehicle's direction of travel and along the horizontal plane (lateral direction of the vehicle), and selecting a positioning satellite with a low elevation angle can improve the accuracy of self-position correction. In light of this, the reference values ​​set here may be set to, for example, ThrPnt = 90 [deg], ThrEle = 10 [deg], and α = 0.5, so that the weighting of the azimuth angle is large.

[0071] In self-localization, the vehicle position within the horizontal plane is mainly estimated. On the other hand, in dead reckoning, the distance traveled based on the sensor output representing the wheel rotation amount is highly reliable, but the position error to the side of the vehicle is likely to be large. Therefore, when correcting the position error due to dead reckoning, it is desirable to correct the position error using a positioning satellite located in the direction to be corrected, i.e., on the side of the vehicle. By using a positioning satellite on or near an extension of the direction to be corrected, the distance between the positioning satellite and the vehicle in the direction to be corrected can be measured more accurately. Therefore, when a positioning satellite on or near an extension of the direction to be corrected is used, the positioning accuracy in the direction to be corrected is improved compared to when a positioning satellite that is not on or near an extension of the direction to be corrected is used.

[0072] For example, when correcting a position error on the side of the vehicle, it is desirable to use a positioning satellite that is to the side of the vehicle rather than directly in front of or above the vehicle, so it is advisable to set the weight related to the azimuth angle in equation (3) to be large. Note that when correcting a position error in the longitudinal direction of the vehicle, it is advisable to use a positioning satellite that is in front of the vehicle, and set the weight related to the azimuth angle in equation (3) to be large. Here, when the reference axis is on the side of the vehicle, the azimuth angle that is in front of the vehicle is 90 degrees in the vehicle's traveling direction. When the reference axis is in the vehicle's traveling direction, the azimuth angle that is in front of the vehicle is 0 degrees.

[0073] In process S15, the target satellite selection unit 12 outputs to the position update unit 13 a message indicating that there are no positioning satellites suitable for use in correction, and ends the process (proceeds to END).

[0074] 5 is a flowchart showing an example of the flow of processing by the position update unit 13 of the self-position estimation device 1. When the position update unit 13 starts the position update processing shown in FIG. 5, first, in process S21, it receives the self-position and stored information obtained from the self-position estimation unit 11, and the satellite selection result obtained from the target satellite selection unit 12.

[0075] Next, in process S22, the position update unit 13 determines whether the selected positioning satellite exists. In process S22, if the satellite selection result indicates that there is no positioning satellite suitable for use in correction (NO), the position update unit 13 does not perform position correction and ends the process (proceeds to END). On the other hand, if the satellite selection result indicates that the selected positioning satellite exists (YES), the position update unit 13 proceeds to process S23.

[0076] In process S23, the position update unit 13 sets a driving trajectory range to be corrected. In process S23, the position update unit 13 references the weight history information obtained from the self-position estimation unit 11 and sets how far back in time the self-position should be from the most recent self-position to perform recalculation. The recalculation range starts from a point where a highly accurate GNSS-measured position is obtained. For example, the recalculation range may be searched from the most recent side for points where the coefficient CG of the position measured by the GNSS receiver 3 is greater than a predetermined threshold, and the first point found may be selected as the starting point. Alternatively, the recalculation range may be searched from the most recent side for points where the ratio CG / CD of the coefficient CG of the position measured by the GNSS receiver 3 to the coefficient CD of the estimated position estimated by the dead reckoning method is greater than a predetermined threshold, and the first point found may be selected as the starting point.

[0077] Next, in step S24, the position update unit 13 calculates the scale factor error and bias error of the on-board sensors such as the gyro sensor and steering angle sensor based on the travel locus range to be corrected and the history information of the self-position or travel distance obtained from the self-position estimation unit 11. This calculation can be performed, for example, by the following procedure. Here, the position at time n is P ｎ , speed is V ｎ The amount of change in azimuth angle from time n to time n+1 is expressed as δθ ｎ＋１ , the rate of change of speed is δa ｎ＋１ The processing period is Δt. The starting point of the travel locus range to be corrected is set to n=0, and the position P ０ , velocity V ０ Then, it can be expressed as the following equations (4) and (5).

[0078]

[0079] That is, position P ｎ＋１ is the speed v per processing period Δt (unit time) ｎ The displacement due to the velocity v ｎ＋１ is the velocity v at the previous time ｎ The speed is obtained by gradually increasing or decreasing the value of the travel path range to be corrected and then slightly rotating the direction. Ｎ , speed is V Ｎ Let the sensitivity error (or scale factor error) of the gyro sensor be err ｍａｇ , and the bias error is err ｂｉａｓ The position and velocity with these errors superimposed thereon can be expressed as in the following equations (6) and (7).

[0080]

[0081] By the way, the position Q of the selected positioning satellite and the position P of the end point of the travel locus range to be corrected from this positioning satellite are Ｎ Since the pseudo distance Dist to is corrected with high accuracy by the positioning augmentation information, the following equation (8) also holds.

[0082]

[0083] That is, the position P of the starting point (base point) ０ is selected in step S23, and δθ ｎ , δa ｎ (n=0 to N) is obtained from the information stored in step S4, and Q and Dist are known because they are determined by the target satellite selection unit 12. Under these conditions, err ｍａｇ , err ｂｉａｓ By calculating the above, the accumulated position error can be eliminated by the autonomous navigation.

[0084] This equation (8) cannot be solved analytically, but for example, it is possible to calculate err for the travel locus range to be corrected by optimization calculation such as GRG (Generalized Reduced Gradient method) nonlinear optimization. ｍａｇ , errｂｉａｓ It should be noted that by making assumptions when solving, it becomes easier to find a solution even when there are only a few selected satellites. For example, when there is only one selected satellite, it may be assumed that the travel route is a horizontal plane.

[0085] In this way, the position update unit 13 calculates a first correction amount corresponding to the scale factor error of the sensor 2 (e.g., sensitivity error of the gyro sensor) and a second correction amount corresponding to the bias error of the sensor 2, and updates the self-position using the first correction amount and the second correction amount. Then, the results of calculating the first correction amount (scale factor error) and the second correction amount (bias error) are sent to process S25.

[0086] Next, in step S25, the position update unit 13 recalculates and updates the output position. In this step S25, the position update unit 13 calculates the position P of the start point of the travel locus range to be corrected based on the scale factor error, the bias error, and the travel distance and travel speed stored in the self-position estimation unit 11. ０ The position update unit 13 recalculates the amount of movement from the self-position estimation unit 11. Specifically, the calculation may be performed according to the above-mentioned formula (1). The position calculated in this way is output instead of the position output from the self-position estimation unit 11. When the process S25 is completed, the series of processes ends (proceed to END). Furthermore, the position update unit 13 may update the self-position stored inside the self-position estimation unit 11.

[0087] [Specific Example of Operation of Self-Localization Estimation Device] Figure 6 is a diagram that schematically illustrates the operation of the self-localization estimation device 1. The operation will be described below with reference to this diagram. First, a vehicle 61 traveling in an environment free of obstructions or diffraction, where GNSS positioning can be performed well, travels while performing GNSS positioning. At this time, the weight of the GNSS-measured position is sufficiently large compared to the weight of the position obtained by dead reckoning. It is also assumed that the positioning augmentation signal is received without any problems and is available for use.

[0088] Next, when the vehicle 62 approaches the entrance to an obstacle such as a tunnel, the environment is such that GNSS positioning can be performed well at this point, but the accuracy begins to deteriorate after measuring its own position several times. For example, the measurement frequency is 1 to 5 times per second.

[0089] When the vehicle 62 completes its entry into an obstacle 63 such as a tunnel, GNSS positioning becomes impossible. The weight of the position based on dead reckoning becomes greater than the weight of the GNSS-measured position, and the vehicle shifts to self-position estimation based mainly on dead reckoning. That is, the position error gradually accumulates due to the influence of the sensitivity error (scale factor error) and bias error of the gyro sensor. When the vehicle 62 travels a certain distance and exits the obstacle 63 such as a tunnel, the accumulated position error causes the self-position estimation unit 11 to hold a vehicle position 64 with a large error. Inside the obstacle 63 such as a tunnel, the target satellite selection unit 12 does not select a positioning satellite, and therefore the position update unit 13 does not perform a position update.

[0090] When the vehicle travels a certain distance and passes through an obstacle 63 such as a tunnel, the target satellite selector 12 selects a positioning satellite 65 (position Q described above) whose positioning augmentation information is still valid, which can be observed, and whose azimuth and elevation angles from the vehicle satisfy predetermined conditions. Line segment D1 indicates a reference axis set in the first direction (lateral direction of the vehicle). Since the pseudo-distance (the pseudo-distance Dist described above) of the vehicle position can be obtained from the positioning satellite 65, a sphere 66 can be calculated with the positioning satellite 65 as its center and the pseudo-distance to the vehicle as its radius.

[0091] The sensitivity error (scale factor error) and bias error of the gyro sensor are calculated based on stored self-position information from a vehicle 62 approaching an entrance to an obstruction 63 such as a tunnel to its own position 64, the position of a positioning satellite 65, and a sphere 66. Based on the calculated sensitivity error (scale factor error) and bias error of the gyro sensor, dead reckoning is recalculated from the position of the vehicle 62, and a vehicle position 67 recalculated so as to approach a sphere 66 with a radius equal to the pseudo distance from the positioning satellite 65 is output from the position update unit 13.

[0092] 1 can quickly eliminate position errors accumulated during autonomous driving near tunnel entrances or in built-up areas where the number of visible satellites is likely to change, at the tunnel exit point, a point where the obstruction by buildings is lifted, etc. Furthermore, various other application scenarios are conceivable, such as when driving on a highway with soundproof walls, or when positioning radio waves can be received only from positioning satellites on either the left or right side of the traveling direction.

[0093] In a typical self-location estimation method, at least four or more visible satellites are required to resolve position errors accumulated by autonomous navigation, and it is necessary to wait until these satellites are stably observed. In contrast, in the self-location estimation device 1 of this embodiment, it is sufficient to have at least one visible positioning satellite that has a good positional relationship with the vehicle and from which positioning augmentation information can be used. This embodiment has the advantage of shortening the wait time and enabling quick error resolution, as it is not necessary to wait until the satellite positioning environment is stable.

[0094] Second Embodiment A second embodiment of a self-location estimation device according to the present disclosure will now be described with reference to Fig. 7. Fig. 7 is a block diagram showing an example configuration of a self-location estimation system including a self-location estimation device according to the second embodiment of the present invention. A self-location estimation system 10A according to this embodiment is configured with a self-location estimation device 1A, a sensor 2, a GNSS receiver 3, and a communication device 4.

[0095] The self-location estimation device 1A according to this embodiment differs from the self-location estimation device 1 according to the first embodiment in that it further includes a receiving unit that receives data transmitted from the communication device 4. This receiving unit can be realized using a network interface 27 (see FIG. 2 ). Other aspects of the self-location estimation device 1A are similar to those of the self-location estimation device 1 according to the first embodiment, and therefore similar parts are denoted by the same reference numerals and description thereof will be omitted.

[0096] In the first embodiment, the GNSS receiver 3 receives radio waves transmitted from positioning satellites as positioning augmentation signals. However, the positioning augmentation information may be acquired by other means. For example, the self-location estimation device 1A may acquire information provided by a service provider via the Internet, or may acquire the information through vehicle-to-vehicle (V2V) communication or road-to-vehicle (I2V) communication. The service provider's communication equipment, communication equipment mounted on other vehicles, and communication equipment installed on roads each correspond to the communication device 4. Although the self-location estimation device 1A acquires the positioning augmentation information via a different route, its operation is essentially the same as that of the self-location estimation device 1.

[0097] On the other hand, in this embodiment, the self-location estimation device 1A receives the positioning augmentation information by a method other than via a positioning satellite, and therefore, even if the self-location estimation device 1A is blocked for a period of time longer than the validity time of the positioning augmentation information, the self-location estimation device 1A can update the positioning augmentation information as appropriate from the communication device 4. This has the effect of enabling the self-location estimation device 1A to quickly resolve errors when the blockage is removed.

[0098] <Third embodiment> A third embodiment of a self-location estimation device 1 according to the present disclosure will be described below with reference to Fig. 8. Fig. 8 is a block diagram showing an example configuration of a self-location estimation system including a self-location estimation device according to the third embodiment of the present invention. A self-location estimation system 10B according to this embodiment is configured from a self-location estimation device 1B, a sensor 2, a GNSS receiver 3, and a map database ("DB" in the figure) 5.

[0099] The self-location estimation device 1B according to this embodiment differs from the self-location estimation device 1 according to the first embodiment in that map data is acquired from a map database 5. The map database 5 can be stored in non-volatile storage (not shown) of the self-location estimation system 10B. Other aspects of the self-location estimation device 1B are similar to those of the self-location estimation device 1 according to the first embodiment, and therefore similar parts are denoted by the same reference numerals and description thereof will be omitted.

[0100] In the first embodiment, the target satellite selection unit 12 does not particularly distinguish between left and right, but the target satellite selection unit 12 may distinguish between left and right by referring to map information. For example, assume that a vehicle is traveling on a two-way road with one lane in each direction, in accordance with the laws and regulations of the target country. In Japan, vehicles drive on the left side of the road. If sound barriers are located on both sides of a tunnel immediately after the exit, the sound barrier on the right side is farther away than the sound barrier on the left side, resulting in a smaller elevation angle from the vehicle's perspective and less likely to block the positioning satellite. In this case, if positioning satellites with valid positioning augmentation information and the same elevation angle exist on both sides of the vehicle's traveling direction, the target satellite selection unit 12 is more likely to select the positioning satellite on the right side of the vehicle's traveling direction. This increases the accuracy and reliability of the position update performed by the position update unit 13.

[0101] Specifically, in the above-mentioned process S14 (see FIG. 4 ), the target satellite selection unit 12 calculates the evaluation value of each positioning satellite as follows: Using a reference value ThrPntR for the azimuth to the right of the vehicle's traveling direction, a reference value ThrPntL for the azimuth to the left of the vehicle's traveling direction, a reference value ThrEle for the elevation angle, and an adjustment coefficient α for the azimuth angle and elevation angle, the target satellite selection unit 12 calculates the evaluation value of each positioning satellite using the following formula (9) or formula (10).

[0102] Here, the evaluation value of positioning satellite N is EvaN, the azimuth angle is PntN, and the elevation angle is EleN. The adjustment coefficient for selecting the right or left positioning satellite is β. As mentioned above, making it easier to select the positioning satellite on the right side of the vehicle's traveling direction means setting this adjustment coefficient β to 1.0 or more.

[0103] (When the positioning satellite that calculates the evaluation value is on the right side of the vehicle's direction of travel)

[0104] (When the positioning satellite that calculates the evaluation value is on the left side of the vehicle's direction of travel)

[0105] This embodiment is characterized in that the evaluation value EvaN calculated in this manner makes it easier to select a positioning satellite on one side of the vehicle's traveling direction.

[0106] To achieve the above, as shown in FIG. 8 , the self-location estimation device 1B has a map database 5 in which lane number information is recorded. The target satellite selection unit 12 is connected to the sensor 2, the GNSS receiver 3, and the map database 5. The target satellite selection unit 12 acquires lane number information on the road the vehicle is traveling on from map data (map information) in the map database 5 based on the vehicle position and traveling direction, and determines from this lane number information whether the road on which the vehicle is traveling is a one-lane two-way road or a one-lane alternating road. If the vehicle is traveling on a one-lane two-way road or a one-lane alternating road, the target satellite selection unit 12 selects a positioning satellite on the opposite side of the road (e.g., the right side in the case of left-hand traffic) from the legally determined driving direction.

[0107] In this way, the target satellite selection unit 12 further selects the target positioning satellite using the vehicle's own position (e.g., vehicle position, driving direction) and map information of the location where the vehicle is driving (e.g., lane number information).

[0108] With this configuration, the self-location estimation device 1B can easily select a positioning satellite on the opposite side of the road for each country or region when traveling on a road, which allows the self-location estimation device 1B to select a positioning satellite that is less susceptible to the effects of multipath, thereby improving the accuracy and reliability of position updates.

[0109] However, this embodiment is not limited to roads with one lane in each direction, and can also be applied to roads with two or more lanes in each direction. This embodiment is suitable for use in situations where there are high soundproof walls or multiple buildings near the side of the vehicle's road. Information on road traffic regulations (side of the road) may also be obtained from road traffic information received via broadcast waves or communication device 4 (see FIG. 7).

[0110] The map database 5 may be stored in the nonvolatile storage 24 (see FIG. 2 ) of the self-location estimation device 1B. Furthermore, the map database 5 may be stored in a cloud server (not shown), and the self-location estimation device 1B may download map data from the map database 5 via the network interface 27 as needed.

[0111] <Fourth embodiment> A fourth embodiment of a self-location estimation device according to the present disclosure will be described below with reference to Fig. 9. Fig. 9 is a block diagram showing an example configuration of a self-location estimation system including a self-location estimation device according to the fourth embodiment of the present invention. A self-location estimation system 10C according to this embodiment is composed of a self-location estimation device 1C, a sensor 2, and a GNSS receiver 3.

[0112] The self-location estimation device 1C according to this embodiment differs from the self-location estimation device 1 according to the first embodiment described above in that it further includes an obstruction state determination unit 14, a storage unit 15, and a sensor error correction unit 16. The storage unit 15 can be configured using a non-volatile storage 24 (see FIG. 2 ). Other aspects of the self-location estimation device 1C are similar to those of the self-location estimation device 1 according to the first embodiment described above, and therefore similar parts are denoted by the same reference numerals and description thereof will be omitted.

[0113] In the first embodiment, a modified example was described in which the target satellite selection unit 12 determines whether each positioning satellite has been observed based on observation information from the positioning satellites and sensors such as cameras and LiDAR. In this embodiment, too, the technology described in the first embodiment can be used to determine whether the vehicle has escaped from an obstructed environment in which the positioning satellite direction is obstructed, based on observation information from the positioning satellites and sensors such as cameras and LiDAR. The obstruction state determination unit 14 determines that the obstruction state has been released based on whether positioning satellites can be observed on both sides of the vehicle's traveling direction, at least within a range of 90 degrees to the left and right from a direction (lateral direction) along the ground plane perpendicular to the vehicle's traveling direction to the vehicle's traveling direction. Note that these observable positioning satellites do not need to be reinforcement targets.

[0114] As described above, in this embodiment, the obstruction state determination unit 14 determines whether or not the positioning radio waves from multiple positioning satellites are blocked, and outputs the determination result to the target satellite selection unit 12. Then, when the obstruction state determination unit 14 determines that the obstruction state has been lifted for a predetermined time (a fixed period) or a predetermined distance, the target satellite selection unit 12 selects at least one target positioning satellite. In this example, the obstruction state determination unit 14 determines that the obstruction state has been lifted based on the position information of the positioning satellite contained in the positioning radio waves from that positioning satellite and external environment information from an external environment sensor (camera, LiDAR, etc.) mounted on the vehicle.

[0115] The storage unit 15 stores the sensitivity error (or scale factor error) err of the gyro sensor. ｍａｇ , and bias error err ｂｉａｓ Each time the error information is calculated, the corresponding value and environmental information are stored. The location update unit 13 stores each error information and environmental information in the storage unit 15 when triggered by the vehicle passing through a tunnel exit. Here, the environmental information may be, for example, the air temperature acquired from a thermometer (not shown), the temperature of a circuit board inside the ECU, the temperature inside the vehicle cabin, the output of a hygrometer (not shown), position information such as latitude and longitude, the time elapsed since the vehicle started traveling, etc.

[0116] The sensor error correction unit 16 corrects the measurement error of the on-board sensor based on the sensitivity error (or scale factor error) and bias error of the gyro sensor and environmental information stored in the storage unit 15. This allows the measurement error to be corrected by using the sensitivity error (or scale factor error) and bias error of the gyro sensor stored in the storage unit 15 when the vehicle is traveling in an environment that matches the environmental information. This has the effect of correcting the gyro drift error that depends on fluctuations in the operating environment, enabling accurate dead reckoning.

[0117] As described above, this embodiment further includes a storage unit 15 and a sensor error correction unit 16 that corrects the measurement error of the sensor 2. The position update unit 13 calculates a first correction amount corresponding to the scale factor error of the sensor 2 (e.g., the sensitivity error of the gyro sensor) and a second correction amount corresponding to the bias error of the sensor 2, and the storage unit 15 stores the first correction amount and the second correction amount. The sensor error correction unit 16 corrects the measurement error of the sensor 2 based on the first correction amount and the second correction amount stored in the storage unit 15.

[0118] As described above, the present invention is not limited to the above-described embodiments, and various other modifications and applications are possible without departing from the spirit of the invention as set forth in the claims. For example, the above-described embodiments have been described in detail and specifically to clearly explain the present invention, and are not necessarily limited to those including all of the components described. Furthermore, it is also possible to add, replace, or delete other components to or from part of the configuration of each embodiment.

[0119] In the above-described embodiment, the control lines and information lines are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. In reality, it can be considered that almost all components are connected to each other.

[0120] Furthermore, in this specification, terms such as "parallel" and "orthogonal" are used, but these terms do not mean only "parallel" and "orthogonal" in the strict sense, but also include the meanings of "parallel" and "orthogonal" in the strict sense, and further include the meanings of "approximately parallel" and "approximately orthogonal" within the range in which they can perform their functions.

[0121] REFERENCE SIGNS LIST 1, 1A, 1B, 1C... Self-position estimation device, 2... Sensor, 3... GNSS receiver, 4... Communication device, 5... Map database, 10, 10A, 10B, 10C... Self-position estimation system, 11... Self-position estimation unit, 12... Target satellite selection unit, 13... Position update unit, 14... Shielding state determination unit, 15... Storage unit, 16... Sensor error correction unit, 20... Calculator, 21... CPU, 22... ROM, 23... RAM, 24... Non-volatile storage, 25... Timer, 26... Input / output interface, 27... Network interface, 61... Vehicle, 62... Vehicle, 63... Shield (tunnel), 64... Vehicle position (own vehicle position before update), 65... Positioning satellite, 66... ​​Spherical surface, 67... Vehicle position (own vehicle position after update), D1... First direction

Claims

1. A self-location estimation device comprising: a self-location estimation unit that estimates the self-location of a vehicle based on vehicle information measured by a sensor mounted on the vehicle and observation information output by a receiver that receives positioning radio waves from multiple positioning satellites; a target satellite selection unit that selects a target positioning satellite from multiple positioning satellites based on the azimuth angle and elevation angle of the positioning satellite as seen from the vehicle with a first direction as a reference axis, and the validity of the positioning augmentation information of the positioning satellite; and a position update unit that updates at least the first direction position of the self-location estimated by the self-location estimation unit based on the pseudorange between at least one of the target positioning satellites selected by the target satellite selection unit and the vehicle and the positioning augmentation information.

2. The self-position estimation device according to claim 1, wherein the first direction is a direction perpendicular to the traveling direction of the vehicle and along the ground plane.

3. The self-position estimation device according to claim 2, wherein the target satellite selection unit calculates an evaluation value for each positioning satellite from the azimuth angle and elevation angle of the positioning satellite and their respective reference values, and selects a target positioning satellite based on the evaluation value.

4. The self-location estimation device according to claim 3, wherein the validity of the positioning augmentation information of the positioning satellite is determined based on whether the positioning satellite is a target for augmentation by the positioning augmentation information and whether the validity period of the positioning augmentation information has expired.

5. A self-positioning estimation device as described in claim 1, further comprising an obstruction state determination unit that determines whether the positioning radio waves from the multiple positioning satellites are in an obstructed state, and the target satellite selection unit selects at least one of the target positioning satellites when the obstruction state determination unit determines that the obstruction state has been lifted for a specified time or a specified distance.

6. The self-position estimation device described in claim 5, wherein the obstruction state determination unit determines whether the obstruction state has been lifted based on the position information of the positioning satellite contained in the positioning radio waves from the positioning satellite and external environment information from an external environment sensor mounted on the vehicle.

7. The self-position estimation device according to claim 1, wherein the position update unit calculates a first correction amount corresponding to a scale factor error of the sensor and a second correction amount corresponding to a bias error of the sensor, and updates the self-position using the first correction amount and the second correction amount.

8. The self-location estimation device according to claim 1, wherein the target satellite selection unit receives the positioning augmentation information from an external communication device.

9. The self-position estimation device according to claim 1, wherein the target satellite selection unit further selects the target positioning satellite using the vehicle's own position and map information of the location where the vehicle is traveling.

10. A self-position estimation device as described in claim 1, further comprising: a memory unit; and a sensor error correction unit that corrects the measurement error of the sensor, wherein the position update unit calculates a first correction amount corresponding to a scale factor error of the sensor and a second correction amount corresponding to a bias error of the sensor, the memory unit stores the first correction amount and the second correction amount, and the sensor error correction unit corrects the measurement error of the sensor based on the first correction amount and the second correction amount stored in the memory unit.

11. A method for estimating a vehicle's own position using a self-position estimation device that receives positioning radio waves from multiple positioning satellites and estimates the vehicle's own position, the method comprising: a process for estimating the vehicle's own position based on vehicle information measured by a sensor mounted on the vehicle and observation information output by a receiver that receives positioning radio waves from multiple positioning satellites; a process for selecting a target positioning satellite from the multiple positioning satellites based on the azimuth angle and elevation angle of the positioning satellite as seen from the vehicle with a first direction as a reference axis, and the validity of the positioning augmentation information of the positioning satellite; and a process for updating at least the first direction of the estimated self-position based on the pseudorange between at least one of the selected target positioning satellites and the vehicle and the positioning augmentation information.

Images