Posture estimation device, posture estimation method, and posture estimation program

Abstract

To provide an attitude estimation device that allows accurate attitude estimation regardless of a satellite reception environment and the degree of travel speed.SOLUTION: An attitude estimation device 10 for estimating the attitude of a movable body 1 comprises: a satellite signal acquisition unit 110 that acquires a satellite signal; a relative positioning unit 120 that calculates the relative positional relationship between antennas by using the acquired satellite signal; a velocity vector calculation unit 140 that calculates a three-dimensional velocity vector of the movable body 1 by using the acquired satellite signal; a first attitude estimation unit 130 that estimates the attitude of the movable body 1 by using the positional relationship calculated by the relative positioning unit 120; a second attitude estimation unit 150 that estimates the attitude of the movable body 1 by using the three-dimensional velocity vector calculated by the velocity vector calculation unit 140; and an attitude integration unit 160 that integrates an estimation result from the first attitude estimation unit 130 and an estimation result from the second attitude estimation unit 150 with each other.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a posture estimation device, a posture estimation method, and a posture estimation program. [Background technology]

[0002] Techniques for estimating the attitude of a moving body have been proposed. For example, Patent Document 1 discloses a technique for an attitude information calculation device that calculates attitude information of a moving body, the technique comprising a holding mechanism that maintains the attitude of a GNSS antenna in the vertical direction, an inertial sensor that is fixed to the coordinate system of the moving body and detects attitude fluctuations of the moving body, and a calculation unit that calculates the attitude information of the moving body based on information obtained by the GNSS antenna and information detected by the inertial sensor. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2013-253928 A Summary of the Invention [Problem to be solved by the invention]

[0004] As disclosed in the above-mentioned Patent Document 1, there is a technique for estimating attitude based on a GPS compass, and integrating the estimation result with the measurement value of an inertial sensor to estimate attitude. However, it is difficult to obtain an attitude estimation result using a GPS compass in urban areas where the satellite reception environment is not good. Therefore, there is a risk that the accuracy of the attitude estimation will deteriorate due to drift of the inertial sensor, etc.

[0005] The present invention has been made in consideration of the above points, and aims to provide an attitude estimation device, an attitude estimation method, and an attitude estimation program that enable accurate attitude estimation regardless of the satellite reception environment or the moving speed. [Means for solving the problem]

[0006] An attitude estimation device according to a first aspect of the present invention is an attitude estimation device that estimates the attitude of a moving body, and includes a satellite signal acquisition unit that acquires satellite signals transmitted from positioning satellites and received by a plurality of antennas, a relative positioning unit that calculates a relative positional relationship between the antennas using the satellite signals acquired by the satellite signal acquisition unit, a velocity vector calculation unit that calculates a three-dimensional velocity vector of the moving body using the satellite signals acquired by the satellite signal acquisition unit, a first attitude estimation unit that estimates the attitude of the moving body using the positional relationship calculated by the relative positioning unit, a second attitude estimation unit that estimates the attitude of the moving body using the three-dimensional velocity vector calculated by the velocity vector calculation unit, and an attitude integration unit that integrates the estimation result of the first attitude estimation unit and the estimation result of the second attitude estimation unit.

[0007] A posture estimation device according to a second aspect of the present invention is the posture estimation device according to the first aspect, further comprising a second reliability determination unit that determines reliability of the estimation result of the second posture estimation unit using a magnitude of the three-dimensional velocity vector estimated by the second posture estimation unit.

[0008] A posture estimation device according to a third aspect of the present invention is the posture estimation device according to the second aspect, wherein the posture integration unit assigns a weight based on the reliability determined by the second reliability determination unit to the estimation result of the second posture estimation unit and integrates it with the estimation result of the first posture estimation unit.

[0009] A posture estimation device according to a fourth aspect of the present invention is the posture estimation device according to any of the first to third aspects, further comprising a first reliability determination unit that determines the reliability of the estimation result of the first posture estimation unit using the estimation result or input information of the first posture estimation unit.

[0010] An attitude estimation device according to a fifth aspect of the present invention is an attitude estimation device according to any of the first to fourth aspects, further comprising an inertial sensor information acquisition unit that acquires information measured by an inertial sensor mounted on the moving body, and the attitude integration unit integrates the estimation result of the first attitude estimation unit and the estimation result of the second attitude estimation unit using the information acquired by the inertial sensor information acquisition unit.

[0011] An attitude estimation method according to a sixth aspect of the present invention is an attitude estimation method for estimating the attitude of a moving body, in which a processor calculates a relative positional relationship between multiple antennas using satellite signals transmitted from positioning satellites and received by the antennas, calculates a three-dimensional velocity vector of the moving body using the acquired satellite signals, estimates the attitude of the moving body using the calculated positional relationship, estimates the attitude of the moving body using the calculated three-dimensional velocity vector, and integrates the estimation result using the positional relationship and the estimation result using the three-dimensional velocity vector.

[0012] An attitude estimation program according to a seventh aspect of the present invention is an attitude estimation program for estimating the attitude of a moving body, and causes a computer to function as an attitude estimation device comprising: a satellite signal acquisition unit that acquires satellite signals transmitted from positioning satellites and received by a plurality of antennas; a relative positioning unit that calculates a relative positional relationship between the antennas using the satellite signals acquired by the satellite signal acquisition unit; a velocity vector calculation unit that calculates a three-dimensional velocity vector of the moving body using the satellite signals acquired by the satellite signal acquisition unit; a first attitude estimation unit that estimates the attitude of the moving body using the positional relationship calculated by the relative positioning unit; a second attitude estimation unit that estimates the attitude of the moving body using the three-dimensional velocity vector calculated by the velocity vector calculation unit; and an attitude integration unit that integrates the estimation result of the first attitude estimation unit and the estimation result of the second attitude estimation unit. Effect of the Invention

[0013] According to the present invention, it is possible to provide an attitude estimation device, an attitude estimation method, and an attitude estimation program that enable accurate attitude estimation regardless of the satellite reception environment or the moving speed by integrating the estimation results. [Brief description of the drawings]

[0014] [Figure 1] 1 is a diagram illustrating an overview of a posture estimation device according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram showing a hardware configuration of the posture estimation device. [Diagram 3] FIG. 2 is a block diagram showing an example of a functional configuration of the posture estimation device. [Figure 4] 13 is a flowchart showing a flow of a posture estimation process performed by the posture estimation device. [Diagram 5] FIG. 2 is a block diagram showing an example of a functional configuration of the posture estimation device. [Figure 6] 13 is a flowchart showing a flow of a posture estimation process performed by the posture estimation device. [Figure 7] FIG. 2 is a block diagram showing an example of a functional configuration of the posture estimation device. [Figure 8] 13 is a flowchart showing a flow of a posture estimation process performed by the posture estimation device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Hereinafter, an example of an embodiment of the present disclosure will be described with reference to the drawings. In each drawing, the same or equivalent components and parts are given the same reference numerals. In addition, the dimensional ratios of the drawings are exaggerated for the convenience of explanation and may differ from the actual ratios.

[0016] FIG. 1 is a diagram showing an overview of an attitude estimation device according to this embodiment. The attitude estimation device 10 is a device that estimates the attitude of a vehicle 1, which is an example of a moving body. When estimating the attitude of the vehicle 1, the attitude estimation device 10 uses satellite signals transmitted from positioning satellites and received by a signal receiving device 2 consisting of multiple antennas. The number of antennas provided in the signal receiving device 2 may be two, or three or more. In addition, when estimating the attitude of the vehicle 1, the attitude estimation device 10 may estimate the attitude of the vehicle 1 using information acquired by an inertial sensor 3.

[0017] An example of the configuration of the posture estimation device 10 according to this embodiment will be described below.

[0018] FIG. 2 is a block diagram showing the hardware configuration of posture estimation device 10. As shown in FIG.

[0019] 2, posture estimation device 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, an input unit 15, a display unit 16, and a communication interface (I / F) 17. Each component is connected to each other via a bus 19 so as to be able to communicate with each other.

[0020] The CPU 11 is a central processing unit, and executes various programs and controls each part. That is, the CPU 11 reads a program from the ROM 12 or the storage 14, and executes the program using the RAM 13 as a working area. The CPU 11 controls each of the above components and performs various arithmetic processing according to the program recorded in the ROM 12 or the storage 14. In this embodiment, the ROM 12 or the storage 14 stores an attitude estimation program for estimating the attitude of the vehicle 1.

[0021] The ROM 12 stores various programs and various data. The RAM 13 temporarily stores programs or data as a working area. The storage 14 is configured with a storage device such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory, and stores various programs including an operating system, and various data.

[0022] The input unit 15 includes a pointing device such as a mouse, and a keyboard, and is used to perform various input operations.

[0023] The display unit 16 is, for example, a liquid crystal display, and displays various information. The display unit 16 may function as the input unit 15 by adopting a touch panel system.

[0024] The communication interface 17 is an interface for communicating with other devices, and uses standards such as Ethernet (registered trademark), FDDI, and Wi-Fi (registered trademark).

[0025] When executing the above posture estimation program, posture estimation device 10 realizes various functions using the above hardware resources.

[0026] Next, the functional configuration of posture estimation device 10 will be described.

[0027] FIG. 3 is a block diagram showing an example of the functional configuration of posture estimation device 10.

[0028] 3, attitude estimation device 10 has, as its functional components, a satellite information acquisition unit 110, a relative positioning unit 120, a first attitude estimation unit 130, a velocity vector calculation unit 140, a second attitude estimation unit 150, and an attitude integration unit 160. Each functional component is realized by CPU 11 reading out and executing an attitude estimation program stored in ROM 12 or storage 14.

[0029] The satellite information acquisition unit 110 acquires satellite signals transmitted from positioning satellites and received by a signal receiving device 2 that is made up of multiple antennas.

[0030] The relative positioning unit 120 calculates the relative positional relationship between the antennas using the satellite signals acquired by the satellite signal acquisition unit 110. Specifically, the relative positioning unit 120 estimates the relative positional relationship between the multiple antennas based on the carrier phases of the satellite signals acquired by the satellite signal acquisition unit 110.

[0031] In general, when there are two antennas, A and B, the following equation (1) is obtained by taking the double difference of the carrier phase of the satellite signals received by the two antennas.

[0032]

number

[0033] In formula (1), DDΦ is ​​the double difference of the carrier phase, ρ is the distance between the antenna and the positioning satellite, c is the speed of light, f is the frequency of the satellite signal, and N is an integer bias. i A , ρ i B are as follows:

[0034]

number

[0035] X sat is the position of the navigation satellite, and X A is the position of antenna A, and ΔX B is the relative position of antenna B with respect to antenna A. The subscripts i and j are the indexes of the primary and secondary satellites, respectively, and A and B indicate antennas A and B, respectively.

[0036] Antenna A position X Acan be considered known since it can be obtained by general satellite positioning using pseudo distances or the like. Therefore, in the above formula (1), the only unknown parameter is the position of antenna B. Therefore, the relative positioning unit 120 can solve the unknown parameters by solving the above formula (1) simultaneously for the number of satellites.

[0037] Even if the number of antennas is three (antennas A, B, and C), the relative positioning unit 120 can obtain the relative positional relationship between antennas A, B, and C by similarly performing relative positioning between antennas A and B, and between antennas A and C.

[0038] The first attitude estimation unit 130 estimates the attitude of the moving object 1 by using the relative positional relationship between the antennas calculated by the relative positioning unit 120. Specifically, the first attitude estimation unit 130 calculates two of the three-axis attitudes (yaw, roll, pitch) when there are two antennas, and calculates all of the three-axis attitudes when there are three antennas.

[0039] The velocity vector calculation unit 140 calculates the three-dimensional velocity vector of the moving object 1 using the satellite signals acquired by the satellite signal acquisition unit 110. Specifically, the velocity vector calculation unit 140 estimates the three-dimensional velocity vector of the moving object 1 based on the Doppler shift of the carrier wave of the satellite signal. The following formula (2) shows the relationship between the Doppler shift of the satellite and the three-dimensional velocity vector V of the moving object 1.

[0040]

number

[0041] In formula (2), i is the satellite index (i = 1, , N), and N is the number of satellites that can be observed at one time. iis a line-of-sight unit vector (dimensionless) between the positioning satellite and the moving body 1, V is a three-dimensional velocity vector (unit [m / s]) of the moving body 1, τ is a clock error change rate (dimensionless) of the signal receiving device 2 called clock drift, and c is the speed of light [m / s]. i , G i are as follows:

[0042]

number

[0043] X ’ i is the position of the positioning satellite, and x is the position of the mobile unit 1. D i is the Doppler shift of the positioning satellite, f1 is the carrier frequency of the positioning satellite (Hz), and G i is a unit vector, and v ’ i is the three-dimensional velocity vector of the positioning satellite. i can be obtained using the positions of the positioning satellites and the position of the moving body 1.

[0044] In formula (2), the unknown parameters are the three-dimensional velocity vector V of the moving object 1 and the clock drift τ, which are a total of four. Since the same number of simultaneous equations as the number of observable satellites can be used, the velocity vector calculation unit 140 can solve these unknown parameters if there are at least four positioning satellites.

[0045] The second attitude estimation unit 150 estimates the attitude of the moving body 1 using the three-dimensional velocity vector of the moving body 1 calculated by the velocity vector calculation unit 140. Specifically, the second attitude estimation unit 150 calculates the yaw angle and pitch angle of the moving body 1 from the azimuth direction and gradient direction of the three-dimensional velocity vector of the moving body 1 calculated by the velocity vector calculation unit 140, respectively.

[0046] Attitude integration section 160 integrates the attitude estimation result of moving object 1 by first attitude estimation section 130 and the attitude estimation result of moving object 1 by second attitude estimation section 150. Specifically, attitude integration section 160 integrates the attitude estimation result by first attitude estimation section 130 and the attitude estimation result by second attitude estimation section 150 by multiplying them by predetermined weights. The predetermined weights are, for example, 1 / 2 for each.

[0047] 3, the attitude estimation device 10 according to this embodiment estimates the attitude of the moving object 1 based on multiple pieces of information and integrates the estimation results. By integrating the estimation results, the attitude estimation device 10 according to this embodiment enables accurate attitude estimation regardless of the satellite reception environment or the moving speed.

[0048] Next, the operation of the posture estimation device 10 will be described.

[0049] 4 is a flowchart showing the flow of the posture estimation process by posture estimation device 10. CPU 11 reads out a posture estimation program from ROM 12 or storage 14, deploys it in RAM 13, and executes it, thereby performing the posture estimation process.

[0050] The CPU 11 acquires a satellite signal transmitted from a positioning satellite and received by the signal receiving device 2 (step S101).

[0051] Following step S101, the CPU 11 uses the acquired satellite signals to calculate the relative positional relationship between the multiple antennas provided in the signal receiving device 2 (step S102). The method of calculating the relative positional relationship between the antennas is the same as that described in the description of the relative positioning unit 120.

[0052] Following step S102, the CPU 11 estimates the attitude of the moving object 1 using the calculated relative positional relationship between the antennas (step S103). The method of estimating the attitude of the moving object 1 using the relative positional relationship between the antennas is the same as that described in the description of the first attitude estimation unit 130.

[0053] Furthermore, following step S101, the CPU 11 uses the acquired satellite signals to calculate a three-dimensional velocity vector of the moving object 1 (step S104). The method of calculating the three-dimensional velocity vector of the moving object 1 is the same as that shown in the explanation of the velocity vector calculation unit 140.

[0054] Following step S104, the CPU 11 estimates the posture of the moving body 1 using the three-dimensional velocity vector of the moving body 1 (step S105). The method of estimating the posture of the moving body 1 using the three-dimensional velocity vector is the same as that described in the description of the second posture estimation unit 150.

[0055] After estimating the posture of the moving object 1 in steps S103 and S105, the CPU 11 integrates the respective estimation results (step S111). The method of integrating the estimation results of the posture of the moving object 1 is the same as that shown in the description of the posture integration unit 160.

[0056] 4, the attitude estimation device 10 according to this embodiment estimates the attitude of the moving object 1 based on multiple pieces of information and integrates the estimation results. By integrating the estimation results, the attitude estimation device 10 according to this embodiment enables accurate attitude estimation regardless of the satellite reception environment or the moving speed.

[0057] In the above description, the attitude estimation result using the relative positional relationship between the antennas and the attitude estimation result using the three-dimensional velocity vector of the moving object 1 are integrated by applying a weight of 1 / 2 to each of them, but the present invention is not limited to this example. For example, the attitude estimation device 10 may integrate the two estimation results after setting a weight according to the magnitude of the three-dimensional velocity vector.

[0058] FIG. 5 is a block diagram showing an example of the functional configuration of posture estimation device 10.

[0059] 5, attitude estimation device 10 has, as functional components, a satellite information acquisition unit 110, a relative positioning unit 120, a first attitude estimation unit 130, a velocity vector calculation unit 140, a second attitude estimation unit 150, a second reliability determination unit 155, and an attitude integration unit 160. Each functional component is realized by CPU 11 reading out and executing an attitude estimation program stored in ROM 12 or storage 14.

[0060] Posture estimation device 10 shown in Fig. 5 is obtained by adding second reliability determination section 155 to posture estimation device 10 shown in Fig. 3. Here, second reliability determination section 155, which is the added component, will be described.

[0061] The second reliability determination unit 155 determines the reliability of the posture of the moving object 1 estimated by the second posture estimation unit 150 from the magnitude of the three-dimensional velocity vector calculated by the velocity vector calculation unit 140. Specifically, the second reliability determination unit 155 may determine the reliability R so that it is normalized between 0 and 1, as shown in the following formula (3). V is the magnitude of the three-dimensional velocity vector calculated by the velocity vector calculation unit 140. R=1-1 / 1+V (3)

[0062] When determining the reliability, the second reliability determination unit 155 may use information on the moving speed of the moving object 1 acquired from an external sensor such as a vehicle speed pulse. The second reliability determination unit 155 may also determine the reliability of the attitude of the moving object 1 using information such as the number of positioning satellites, the elevation angle, SNR (Signal to Noise Ratio), and DOP (Dilution Of Precision).

[0063] The attitude integration unit 160 weights the attitude estimation result using the three-dimensional velocity vector of the moving object 1 using the reliability R determined by the second reliability determination unit 155, and integrates it with the attitude estimation result using the relative positional relationship between the antennas. For example, when the second reliability determination unit 155 determines the reliability so as to be normalized between 0 and 1, the attitude integration unit 160 may multiply the information on the attitude of the moving object 1 estimated by the second attitude estimation unit 150 by the reliability R as a weight. Furthermore, the attitude integration unit 160 may multiply the information on the attitude of the moving object 1 estimated by the first attitude estimation unit 130 by (1-R) ​​as a weight. Then, the attitude integration unit 160 may obtain the information on the attitude of the moving object 1 by integrating the attitude estimation results after multiplication by the weight.

[0064] The attitude estimation device 10 according to this embodiment has the configuration shown in Fig. 5, and estimates the attitude of the moving body 1 based on multiple pieces of information and integrates the estimation results. Also, the attitude estimation device 10 according to this embodiment has the configuration shown in Fig. 5, and integrates the estimation results based on the reliability of the estimation results of the attitude of the moving body 1 using a three-dimensional velocity vector. By integrating the estimation results, the attitude estimation device 10 according to this embodiment enables accurate attitude estimation regardless of the satellite reception environment or the moving speed.

[0065] 6 is a flowchart showing the flow of the posture estimation process by posture estimation device 10. CPU 11 reads out a posture estimation program from ROM 12 or storage 14, deploys it in RAM 13, and executes it, thereby performing the posture estimation process.

[0066] The flowchart shown in FIG. 6 is obtained by adding the process of step S107 to the flowchart shown in FIG.

[0067] In step S105, the CPU 11 estimates the posture of the moving body 1 using the three-dimensional velocity vector of the moving body 1, and then determines the reliability R of the estimation result of the posture of the moving body 1 using the three-dimensional velocity vector (step S107). The method of determining the reliability of the estimation result of the posture of the moving body 1 using the three-dimensional velocity vector is the same as that described in the description of the second reliability determination unit 155.

[0068] After estimating the attitude of the moving object 1 in steps S103 and S105, the CPU 11 integrates the respective estimation results (step S111). Specifically, the CPU 11 weights the attitude estimation result using the three-dimensional velocity vector of the moving object 1 using the reliability R determined in step S107, and integrates the estimated attitude with the attitude estimation result using the relative positional relationship between the antennas obtained in step S103.

[0069] The attitude estimation device 10 according to this embodiment estimates the attitude of the moving body 1 based on multiple pieces of information and integrates the estimation results by executing the process shown in Fig. 6. Furthermore, the attitude estimation device 10 according to this embodiment integrates the estimation results based on the reliability of the estimation results of the attitude of the moving body 1 using a three-dimensional velocity vector by executing the process shown in Fig. 6. By integrating the estimation results, the attitude estimation device 10 according to this embodiment enables accurate attitude estimation regardless of the satellite reception environment or the moving speed.

[0070] Pose estimation device 10 may also determine the reliability of the posture estimation result using the relative positional relationship between the antennas.

[0071] FIG. 7 is a block diagram showing an example of the functional configuration of posture estimation device 10.

[0072] 7, the attitude estimation device 10 has, as its functional components, a satellite information acquisition unit 110, a relative positioning unit 120, a first attitude estimation unit 130, a first reliability determination unit 135, a velocity vector calculation unit 140, a second attitude estimation unit 150, a second reliability determination unit 155, an attitude integration unit 160, and an inertial sensor information acquisition unit 170. Each functional component is realized by the CPU 11 reading out and executing an attitude estimation program stored in the ROM 12 or the storage 14.

[0073] The posture estimation device 10 shown in Fig. 7 is obtained by adding a first reliability determination unit 135 and an inertial sensor information acquisition unit 170 to the posture estimation device 10 shown in Fig. 5. Here, the added components, first reliability determination unit 135 and inertial sensor information acquisition unit 170, will be described.

[0074] The first reliability determination unit 135 determines the reliability of the attitude of the moving object 1 estimated by the first attitude estimation unit 130, using information used by the first attitude estimation unit 130 to estimate the attitude and the result of the attitude estimation. Specifically, the first reliability determination unit 135 may output 1 if the first attitude estimation unit 130 is able to estimate the attitude, and may output 0 if the first attitude estimation unit 130 is unable to estimate the attitude. The first reliability determination unit 135 may also determine the reliability based on the number of positioning satellites, the elevation angle, the SNR, the DOP, and the like. The first reliability determination unit 135 may also determine the reliability using information on the difference between the positioning result by the relative positioning unit 120 and the distance between known antennas.

[0075] The inertial sensor information acquisition unit 170 acquires information on angular velocity and acceleration from the inertial sensor 3 and sends it to the attitude integration unit 160 .

[0076] The posture integration unit 160 weights and integrates the posture estimation results using the reliability determined by the first reliability determination unit 135 and the reliability determined by the second reliability determination unit 155. Specifically, the posture integration unit 160 integrates the posture estimation results using the following formula (4).

[0077]

number

[0078] In formula (4), P1, P2, P3, and P3' respectively indicate first attitude estimation unit 130, second attitude estimation unit 150, the final attitude estimation result at the current time, and the final attitude estimation result at the previous time. Also, w1 and w2 respectively indicate the weight of the attitude estimation result of first attitude estimation unit 130, the weight of the attitude estimation result of second attitude estimation unit 150, and α indicates the update weight from the result at the previous time. Also, w1 and w2 can be obtained from first reliability determination unit 135 and second reliability determination unit 155, respectively. Also, α is an appropriate coefficient adjusted according to the observation accuracy.

[0079] Furthermore, when using information on angular velocity and acceleration from the inertial sensor information acquisition unit 170, the attitude integration unit 160 integrates the attitude estimation results using the following equation (5).

[0080]

number

[0081] In the above formula (5), P0 is the attitude of the moving body 1 calculated from the inertial sensor 3, and w0 is its weight. w0 may be set to an appropriate fixed value according to the specifications of the inertial sensor 3, or may be a variable amount according to the temperature characteristics of the inertial sensor 3. The other variables in formula (5) are the same as those in formula (4).

[0082] Although the inertial sensor 3 is used in the above example, the present invention is not limited to this example. Instead of the inertial sensor 3, a geomagnetic sensor may be used.

[0083] The attitude estimation device 10 according to this embodiment has the configuration shown in Fig. 7 and estimates the attitude of the moving body 1 based on multiple pieces of information and integrates the estimation results. Also, the attitude estimation device 10 according to this embodiment has the configuration shown in Fig. 7 and integrates the estimation results based on the reliability of the estimation result of the attitude of the moving body 1 using the relative positional relationship between the antennas and the reliability of the estimation result of the attitude of the moving body 1 using a three-dimensional velocity vector. The attitude estimation device 10 according to this embodiment integrates the estimation results based on the reliability, thereby enabling accurate attitude estimation regardless of the satellite reception environment or the moving speed.

[0084] 8 is a flowchart showing the flow of the posture estimation process by posture estimation device 10. CPU 11 reads out a posture estimation program from ROM 12 or storage 14, deploys it in RAM 13, and executes it, thereby performing the posture estimation process.

[0085] The flowchart shown in FIG. 8 is obtained by adding the process of step S106 to the flowchart shown in FIG. 6, and further replacing the process of step S111 with the process of step S112.

[0086] After estimating the attitude of the moving object 1 using the calculated relative positional relationship between the antennas, the CPU 11 determines the reliability of the estimation result of the attitude of the moving object 1 using the relative positional relationship between the antennas (step S106). The method of determining the reliability of the estimation result of the attitude of the moving object 1 using the relative positional relationship between the antennas is the same as that described in the description of the first reliability determination unit 135.

[0087] After determining the reliability of the estimation results of the attitude of the moving body 1 in steps S106 and S107, the CPU 11 integrates the estimation results of the attitude of the moving body 1 (step S112). When integrating the estimation results of the attitude of the moving body 1, the CPU 11 uses information from the inertial sensor 3. The method of integrating the estimation results of the attitude of the moving body 1 is the same as that shown in the description of the attitude integration unit 160 in FIG.

[0088] The attitude estimation device 10 according to this embodiment estimates the attitude of the moving body 1 based on multiple pieces of information and integrates the estimation results by executing the process shown in Fig. 8. Furthermore, the attitude estimation device 10 according to this embodiment integrates the estimation results based on the reliability of the estimation result of the attitude of the moving body 1 using the relative positional relationship between the antennas and the reliability of the estimation result of the attitude of the moving body 1 using a three-dimensional velocity vector by executing the process shown in Fig. 8. The attitude estimation device 10 according to this embodiment integrates the estimation results based on the reliability, thereby enabling accurate attitude estimation regardless of the satellite reception environment or the moving speed.

[0089] In addition, the posture estimation process executed by the CPU by reading the software (program) in each of the above embodiments may be executed by various processors other than the CPU. In this case, examples of the processor include a PLD (Programmable Logic Device) such as an FPGA (Field-Programmable Gate Array) whose circuit configuration can be changed after manufacture, and a dedicated electric circuit such as an ASIC (Application Specific Integrated Circuit) which is a processor having a circuit configuration designed exclusively for executing a specific process. In addition, the posture estimation process may be executed by one of these various processors, or may be executed by a combination of two or more processors of the same or different types (for example, a plurality of FPGAs, a combination of a CPU and an FPGA, etc.). In addition, the hardware structure of these various processors is, more specifically, an electric circuit in which circuit elements such as semiconductor elements are combined.

[0090] In addition, in each of the above embodiments, the posture estimation processing program is prestored (installed) in a ROM or storage, but the present invention is not limited to this. The program may be provided in a form recorded on a non-transitory recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network. [Explanation of symbols]

[0091] 1. Mobile 2. Signal receiving device 3. Inertial Sensor 10 Posture estimation device

Claims

1. A posture estimation device for estimating a posture of a moving object, comprising: a satellite signal acquisition unit that acquires satellite signals transmitted from positioning satellites and received by a plurality of antennas; a relative positioning unit that calculates a relative positional relationship between the antennas by using the satellite signals acquired by the satellite signal acquisition unit; a velocity vector calculation unit that calculates a three-dimensional velocity vector of the moving object using the satellite signals acquired by the satellite signal acquisition unit; a first attitude estimation unit that estimates an attitude of the moving object using the positional relationship calculated by the relative positioning unit; a second attitude estimation unit that estimates an attitude of the moving object by using the three-dimensional velocity vector calculated by the velocity vector calculation unit; a posture integration unit that integrates an estimation result of the first posture estimation unit and an estimation result of the second posture estimation unit; A posture estimation device comprising:

2. The posture estimation device according to claim 1 , further comprising a second reliability determination unit that determines reliability of an estimation result of the second posture estimation unit, using a magnitude of the three-dimensional velocity vector estimated by the second posture estimation unit.

3. The posture estimation device according to claim 2 , wherein the posture integration unit provides a weight based on the reliability determined by the second reliability determination unit to the estimation result of the second posture estimation unit and integrates it with the estimation result of the first posture estimation unit.

4. 4. The posture estimation device according to claim 1, further comprising a first reliability determination unit that determines reliability of the estimation result of the first posture estimation unit, using the estimation result of the first posture estimation unit or input information.

5. An inertial sensor information acquisition unit that acquires information measured by an inertial sensor mounted on the moving body, 5. The posture estimation device according to claim 1, wherein the posture integration unit integrates the estimation result of the first posture estimation unit and the estimation result of the second posture estimation unit using information acquired by the inertial sensor information acquisition unit.

6. A method for estimating the attitude of a moving object, comprising: The processor: Calculating a relative positional relationship between the antennas using satellite signals transmitted from positioning satellites and received by the plurality of antennas; Calculating a three-dimensional velocity vector of the moving object using the acquired satellite signals; Estimating the attitude of the moving object using the calculated positional relationship; Estimating the attitude of the moving object using the calculated three-dimensional velocity vector; Integrating the estimation result using the positional relationship and the estimation result using the three-dimensional velocity vector. Pose estimation method.

7. A posture estimation program for estimating a posture of a moving object, comprising: Computer, a satellite signal acquisition unit that acquires satellite signals transmitted from positioning satellites and received by a plurality of antennas; a relative positioning unit that calculates a relative positional relationship between the antennas by using the satellite signals acquired by the satellite signal acquisition unit; a velocity vector calculation unit that calculates a three-dimensional velocity vector of the moving object using the satellite signals acquired by the satellite signal acquisition unit; a first attitude estimation unit that estimates an attitude of the moving object using the positional relationship calculated by the relative positioning unit; a second attitude estimation unit that estimates an attitude of the moving object by using the three-dimensional velocity vector calculated by the velocity vector calculation unit; a posture integration unit that integrates an estimation result of the first posture estimation unit and an estimation result of the second posture estimation unit; and a posture estimation program for causing the posture estimation device to function as the posture estimation device.

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