Mobile object position estimation device and mobile object position estimation program

Abstract

To estimate a current position of a mobile object with a high degree of accuracy without requiring large scale construction mounting a vehicle speed signal generator in a dead reckoning technology for estimating the current position of the mobile object in the present disclosure.SOLUTION: According to the present disclosure, a mobile object position estimation device 8 comprises a mobile object speed estimation unit 82 that performs weighting addition of speed of a mobile object measured by a radar device 5, speed of the mobile object measured by a satellite positioning device 6 and a time integration value of acceleration of a mobile object measured by an acceleration / angular velocity sensor 7 using a measurement reliability coefficient of the radar device 5, a measurement reliability coefficient of the satellite positioning device 6 and a measurement reliability coefficient of the acceleration / angular velocity sensor 7 as weighting coefficients.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a dead reckoning technique for estimating a current position of a moving object. [Background technology]

[0002] Dead reckoning technology for estimating the current position of a moving object is disclosed in Patent Documents 1 to 3, etc. The dead reckoning technology estimates the current position of a moving object based on the satellite positioning position measured by the satellite positioning device when the satellite positioning device is capable of receiving a positioning satellite signal, and estimates the current position of the moving object using the vehicle speed, acceleration / angular velocity, and the most recently determined position of the moving object when the satellite positioning device is unable to receive a positioning satellite signal.

[0003] The configuration of a conventional mobile object position estimation system is shown in Fig. 1. The procedure of the conventional mobile object position estimation process is shown in Fig. 2. The conventional mobile object position estimation system L1 includes a satellite positioning device 1, a vehicle speed signal generator 2, an acceleration / angular velocity sensor 3, and a mobile object position estimation device 4. The conventional mobile object position estimation device 4 includes a mobile object data acquisition unit 41 and a mobile object position estimation unit 42.

[0004] The mobile object data acquisition unit 41 (1) acquires information on the position of the mobile object and information on the measurement reliability of the satellite positioning device 1 (an approximate value of the accuracy of the positioning position) from the satellite positioning device 1 mounted on the mobile object and measuring the position of the mobile object, (2) acquires information on the speed of the mobile object from a vehicle speed signal generating device 2 mounted on the mobile object and generating a vehicle speed signal based on the number of rotations of the axle, and (3) acquires information on the acceleration and angular velocity of the mobile object from an acceleration / angular velocity sensor 3 mounted on the mobile object and measuring the acceleration and angular velocity of the mobile object (step S1). Note that the acceleration / angular velocity sensor 3 may be a separate sensor or an integrated sensor.

[0005] When the measurement reliability of the satellite positioning device 1 is higher than a predetermined value (step S2, YES), the moving object position estimating unit 42 estimates the current position of the moving object based on the satellite positioning position measured by the satellite positioning device 1 (step S3). When the measurement reliability of the satellite positioning device 1 is lower than a predetermined value (step S2, NO), the moving object position estimating unit 42 estimates the current position of the moving object based on the vehicle speed signal based on the number of rotations of the axle output by the vehicle speed signal generating device 2, the acceleration and angular velocity of the moving object measured by the acceleration / angular velocity sensor 3, and the position of the moving object determined immediately before (step S4). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 5036462 [Patent Document 2] Patent No. 6201762 [Patent Document 3] Patent No. 6215915 Summary of the Invention [Problem to be solved by the invention]

[0007] Here, the vehicle speed signal generator 2 outputs a vehicle speed signal based on the number of revolutions of the axle, and the acceleration / angular velocity sensor 3 measures the acceleration of the moving object including an offset component. It is generally known that the information on the speed of the moving object obtained by time-integrating the acceleration measured by the acceleration / angular velocity sensor 3 includes an accumulated error due to the offset component, and the error accumulates over time. On the other hand, the speed obtained from the vehicle speed signal does not include integration in the calculation process, so errors do not accumulate over time. The moving object position estimator 42 estimates the current position of the moving object based on the speed of the moving object and the angular velocity measured by the acceleration / angular velocity sensor 3, but it is possible to estimate the current position of the moving object more accurately by using the speed of the moving object calculated from the vehicle speed signal output by the vehicle speed signal generator 2 depending on the presence or absence of the accumulated error, than by using the information on the speed of the moving object obtained by time-integrating the acceleration of the moving object measured by the acceleration / angular velocity sensor 3.

[0008] However, some moving objects such as trains, agricultural machines, and construction machines are not equipped with the vehicle speed signal generating device 2, and in order to install the vehicle speed signal generating device 2 in such vehicles, large-scale construction work is required to access the axle drive parts, etc., depending on the vehicle. Even if the vehicle speed signal generating device 2 is installed, there are cases where the vehicle speed cannot be measured accurately due to wheel spin, etc.

[0009] Therefore, in order to solve the above-mentioned problems, the present disclosure aims to use dead reckoning technology for estimating the current position of a moving body to estimate the current position of the moving body with high accuracy without requiring large-scale construction work to install a vehicle speed signal generating device. [Means for solving the problem]

[0010] In order to solve the above problem, instead of acquiring speed information by a vehicle speed signal generator, a radar device acquires speed information. Here, compared to a vehicle speed signal generator, a radar device can be easily installed without requiring large-scale construction, and can acquire speed information by measuring the Doppler shift between an irradiated wave and a reflected wave. The radar device also calculates measurement reliability based on the received power and / or SN ratio of the reflected wave.

[0011] However, it is necessary to consider that the radar device and satellite positioning device may be affected by the external environment of the moving object, and the speed accuracy and positioning accuracy (position, speed, time, etc.) may deteriorate. In addition, when integrating the acceleration sensor value, it is necessary to consider that errors may accumulate over time, as described above. Therefore, the current speed of the moving object is estimated by weighting and adding the speed of the moving object measured by the radar device, the speed of the moving object measured by the satellite positioning device, and the time integral value of the acceleration of the moving object measured by the acceleration sensor according to the measurement reliability based on the reception power and / or S / N ratio of the reflected wave of the radar device, the measurement reliability of the satellite positioning device, and the acceleration integration time of the acceleration sensor.

[0012] Specifically, the present disclosure provides a mobile body data acquisition unit that (1) acquires, from a radar device mounted on the mobile body and measuring the speed of the mobile body, information on the speed of the mobile body and information on measurement reliability based on the reception power and / or SN ratio of the reflected wave of the radar device, (2) acquires, from a satellite positioning device mounted on the mobile body and measuring positioning information of the mobile body, information on the speed of the mobile body and information on the measurement reliability of the satellite positioning device, (3) acquires information on the acceleration of the mobile body from an acceleration sensor mounted on the mobile body and measuring the acceleration of the mobile body, and (4) acquires information on the angular velocity of the mobile body from an angular velocity sensor mounted on the mobile body and measuring the angular velocity of the mobile body; and (1) calculates a measurement reliability coefficient of the radar device based on the measurement reliability based on the reception power and / or SN ratio of the reflected wave of the radar device, and (2) calculates a measurement reliability coefficient based on the measurement reliability of the satellite positioning device. (3) calculates a measurement reliability coefficient of the acceleration sensor based on the acceleration integration time of the acceleration sensor; and (4) a moving body speed estimating unit that weights and adds together the time integral values ​​of the speed of the moving body measured by the radar device, the speed of the moving body measured by the satellite positioning device, and the acceleration of the moving body measured by the acceleration sensor using the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor as weighting coefficients, and a moving body position estimating unit that estimates the current position of the moving body based on the time integral value of the speed of the moving body estimated by the moving body speed estimating unit through the weighting addition, the time integral value of the angular velocity of the moving body measured by the angular velocity sensor, and the position of the moving body determined immediately before.

[0013] According to this configuration, the current position of the moving object can be estimated with high accuracy without requiring large-scale construction to install a vehicle speed signal generator. If the configuration is such that the speed of the moving object with the highest measurement reliability coefficient is simply adopted, discontinuity in the speed of the moving object may occur when switching the speed of the moving object with the highest measurement reliability coefficient, due to the radar device, the satellite positioning device, and the acceleration sensor each measuring the speed independently. On the other hand, by adopting a configuration in which the speed of the moving object is weighted and added according to the measurement reliability coefficient in the present disclosure, if the method of calculating the measurement reliability coefficient is devised as specifically shown below, discontinuity in the speed of the moving object does not occur, and the speed of the moving object can be seamlessly estimated.

[0014] The present disclosure also relates to a mobile object position estimation device, characterized in that the mobile object speed estimation unit (1) calculates a measurement reliability coefficient of the radar device to be larger / smaller as the measurement reliability based on the received power and / or SN ratio of the reflected wave of the radar device is higher / lower, (2) calculates a measurement reliability coefficient of the satellite positioning device to be larger / smaller as the measurement reliability of the satellite positioning device is higher / lower, and (3) calculates a measurement reliability coefficient of the acceleration sensor to be larger / smaller as the acceleration integration time after offset removal of the acceleration sensor is shorter / longer.

[0015] According to this configuration, a weighting coefficient for the current speed of the moving body obtained by multiple types of speed measurement means can be calculated depending on the influence of the external environment of the moving body (radar device and satellite positioning device) or depending on the length of the acceleration accumulation time (acceleration sensor), and the current speed of the moving body obtained by multiple types of speed measurement means can be weighted and added seamlessly.

[0016] The present disclosure also relates to a mobile object position estimation device, characterized in that the mobile object speed estimation unit recalculates the sum of the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor to a constant (including 1) and uses this as the weighting coefficient.

[0017] According to this configuration, the weighting coefficients of the current speed of the moving object obtained by multiple types of speed measurement means are recalculated so that the total value becomes a constant (including 1), and the current speeds of the moving object obtained by multiple types of speed measurement means can be weighted and added seamlessly.

[0018] The present disclosure also relates to a mobile object position estimation device, characterized in that the mobile object speed estimation unit (1) sets the maximum possible values ​​for the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor to equal values, or (2) sets the maximum possible values ​​for the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor to different values ​​depending on the priority order of the radar device, the satellite positioning device, and the acceleration sensor.

[0019] According to this configuration, it is not necessary to prioritize the radar device, the satellite positioning device, and the acceleration sensor depending on the estimation accuracy of the speed of the moving body, and priorities may be assigned to the radar device, the satellite positioning device, and the acceleration sensor, or the priorities may be in any order.

[0020] The present disclosure also provides a mobile object position estimation program for causing a computer to execute each processing step performed by each processing unit included in the mobile object position estimation device described above.

[0021] According to this configuration, it is possible to provide a program having the effects described above.

[0022] The above disclosed inventions can be combined to the greatest extent possible. Effect of the Invention

[0023] In this way, the present disclosure provides a dead reckoning technology for estimating the current position of a moving body, which is capable of estimating the current position of a moving body with high accuracy without requiring large-scale construction work to install a vehicle speed signal generating device. [Brief description of the drawings]

[0024] [Figure 1] FIG. 1 is a diagram showing a configuration of a mobile object position estimation system according to a conventional technique. [Diagram 2] FIG. 1 is a diagram showing a procedure of a moving object position estimation process according to the prior art; [Diagram 3] 1 is a diagram illustrating a configuration of a moving object position estimation system according to the present disclosure. [Figure 4] FIG. 2 is a diagram showing a procedure of a moving object position estimation process according to the present disclosure. [Diagram 5] FIG. 11 is a diagram showing a specific example of a calculation process for a measurement reliability coefficient of a speed obtained by the radar device of the present disclosure. [Figure 6] 11 is a diagram showing a specific example of a calculation process of a measurement reliability coefficient of a speed acquired by a satellite positioning device of the present disclosure. FIG. [Figure 7] FIG. 13 is a diagram showing a specific example of a calculation process for a measurement reliability coefficient of an acceleration integral value according to the present disclosure. [Figure 8] FIG. 11 is a diagram showing a specific example of a calculation process of a measurement reliability coefficient for a speed acquired by a radar device of the present disclosure, and a speed and an acceleration integral value acquired by a satellite positioning device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0025] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present disclosure will be described with reference to the accompanying drawings. The embodiments described below are examples of the present disclosure, and the present disclosure is not limited to the following embodiments.

[0026] (Configuration of the mobile object position estimation system of the present disclosure) The configuration of a mobile object position estimation system according to the present disclosure is shown in Fig. 3. The mobile object position estimation system L2 according to the present disclosure includes a radar device 5, a satellite positioning device 6, an acceleration / angular velocity sensor 7, and a mobile object position estimation device 8. The mobile object position estimation device 8 according to the present disclosure includes a mobile object data acquisition unit 81, a mobile object speed estimation unit 82, and a mobile object position estimation unit 83.

[0027] The moving object is, but is not limited to, a train, an agricultural machine, a construction machine, an automobile, etc. The radar device 5 is a radar device or the like connected to the outside of the moving object position estimation device 8. The satellite positioning device 6 is a GNSS receiver or the like connected to the outside of the moving object position estimation device 8. The acceleration / angular velocity sensor 7 is an inertial sensor or the like built into the moving object position estimation device 8. The acceleration / angular velocity sensor 7 may be a separate sensor or an integrated sensor. The moving object position estimation device 8 can be realized by installing the moving object position estimation program shown in FIG. 4 in a computer.

[0028] That is, instead of acquiring the speed information by the vehicle speed signal generator 2, the radar device 5 acquires the speed information. Here, the radar device 5 can be easily installed without requiring large-scale construction, compared to the vehicle speed signal generator 2, and can acquire the speed information by measuring the Doppler shift between the irradiated wave and the reflected wave. The radar device 5 also calculates the measurement reliability based on the received power and / or the SN ratio of the reflected wave.

[0029] However, it is necessary to consider that the radar device 5 and the satellite positioning device 6 may be affected by the external environment of the moving object and may deteriorate in speed accuracy and positioning accuracy (position, speed, time, etc.). In addition, when integrating the acceleration sensor value, it is necessary to consider that errors may accumulate over time as described above. Therefore, the speed of the moving object measured by the radar device 5, the speed of the moving object measured by the satellite positioning device 6, and the time integral value of the acceleration of the moving object measured by the acceleration / angular velocity sensor 7 are weighted and added according to the measurement reliability based on the reception power and / or SN ratio of the reflected wave of the radar device 5, the measurement reliability (reference value of the accuracy of the positioning position) of the satellite positioning device 6, and the acceleration integration time of the acceleration / angular velocity sensor 7, to estimate the current speed of the moving object. The procedure of the moving object position estimation process of the present disclosure will be specifically described below.

[0030] (Procedure of mobile object position estimation process according to the present disclosure) The procedure of the moving body position estimation process of the present disclosure is shown in FIG. RThe radar device 5 measures the speed V R (2) obtains the speed V of the moving object from a satellite positioning device 6 mounted on the moving object and measuring the positioning information (position, speed, time, etc.) of the moving object. G (3) obtain information on the acceleration a and angular velocity ω of the moving body from the acceleration / angular velocity sensor 7 mounted on the moving body and measuring the acceleration a and angular velocity ω of the moving body (step S5).

[0031] The moving object speed estimation unit 82 (1) calculates a measurement reliability coefficient C R (Step S6), and (2) calculate the measurement reliability coefficient C of the satellite positioning device 6 based on the measurement reliability of the satellite positioning device 6. G (Step S7), and (3) calculate the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 based on the acceleration integration time of the acceleration / angular velocity sensor 7. A Calculate (step S8).

[0032] The moving object speed estimation unit 82 estimates the measurement reliability coefficient C R , the measurement reliability coefficient C of the satellite positioning device 6 G and the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 A The moving object speed estimating unit 82 recalculates the sum of the measurement reliability coefficient C R ' and the measurement reliability coefficient C of the satellite positioning device 6 G ' and the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 A ' and C R '+C G '+C A ' = constant (including 1).

[0033] The moving object speed estimation unit 82 estimates the measurement reliability coefficient C R ', the measurement reliability coefficient C of the satellite positioning device 6 G' and the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 A ' is used as a weighting coefficient, and the speed V of the moving object measured by the radar device 5 is R , the speed V of the moving object measured by the satellite positioning device 6 G and the time integral value ∫adt of the acceleration a of the moving object measured by the acceleration / angular velocity sensor 7 is weighted and added to obtain the current velocity V t (Step S10). Here, the current speed V t V t =C R 'V R +C G 'V G +C A The time integral value ∫adt of the acceleration a of the moving body is the integral value from the initial time 0 to the current time t.

[0034] The moving object position estimation unit 83 estimates the moving object's speed (initial speed V0 to current speed V t ), the time integral value of the angular velocity ω of the moving body measured by the acceleration / angular velocity sensor 7, and the position of the moving body determined immediately before (in the initial stage of the moving body position estimation process, the satellite positioning device 6 can measure it. In the steady stage of the moving body position estimation process, the radar device 5, the satellite positioning device 6, and the acceleration / angular velocity sensor 7 can measure it in the previous step S11.) based on this, the current position of the moving body is estimated (this time step S11).

[0035] Therefore, the current position of the moving object can be estimated with high accuracy without requiring large-scale construction to install the vehicle speed signal generating device 2. Here, if the configuration is such that the speed of the moving object with the highest measurement reliability coefficient is simply adopted, discontinuity in the speed of the moving object may occur when switching the speed of the moving object with the highest measurement reliability coefficient, due to the fact that the radar device 5, the satellite positioning device 6, and the acceleration / angular velocity sensor 7 each measure the speed independently. On the other hand, by adopting a configuration in which the speed of the moving object is weighted and added according to the measurement reliability coefficient in the present disclosure, and by devising a method for calculating the measurement reliability coefficient as specifically shown below, discontinuity in the speed of the moving object does not occur, and the speed of the moving object can be seamlessly estimated.

[0036] (Specific example of calculation process of speed measurement reliability coefficient obtained by the radar device of the present disclosure) A specific example of a calculation process of the measurement reliability coefficient of the speed obtained by the radar device of the present disclosure is shown in Fig. 5. The moving object speed estimation unit 82 calculates the measurement reliability coefficient C R (Furthermore, the measurement reliability coefficient C R Then, calculate whether to make it larger or smaller (step S6).

[0037] In the upper part of FIG. 5, the radar device 5 is mounted on the front of the vehicle V, and is able to irradiate a radar to a reflecting object on the road surface R and receive a reflected wave with sufficient strength. Therefore, the radar device 5 sets the measurement reliability of the radar device 5 high based on the reception power and / or the SN ratio of the reflected wave. Then, the moving object speed estimation unit 82 calculates the measurement reliability coefficient C R (Furthermore, the measurement reliability coefficient C R ') is calculated large (step S6).

[0038] In the lower section of FIG. 5, the radar device 5 is mounted on the front of the vehicle V and irradiates a radar to a reflective object on the road surface R. However, the reflected wave cannot be received with sufficient strength because the reflective object on the road surface R is blocked by snowfall P. Therefore, the radar device 5 sets the measurement reliability of the radar device 5 low based on the reception power and / or the SN ratio of the reflected wave. Then, the moving object speed estimation unit 82 calculates the measurement reliability coefficient C R (Furthermore, the measurement reliability coefficient C R ') is calculated to be smaller (step S6).

[0039] Therefore, depending on the influence of the external environment of the moving body, a weighting coefficient for the speed of the moving body measured by the radar device 5 can be calculated, and the weight of the speed of the moving body measured by the radar device 5 can be set among the current speeds of the moving body obtained by multiple types of speed measurement means that are weighted and added.

[0040] (Specific example of calculation process of speed measurement reliability coefficient obtained by the satellite positioning device of the present disclosure) A specific example of a calculation process of the measurement reliability coefficient of the speed acquired by the satellite positioning device of the present disclosure is shown in Fig. 6. The moving object speed estimation unit 82 calculates the measurement reliability coefficient C G (Furthermore, the measurement reliability coefficient C G Then, calculate whether to make it larger or smaller (step S7).

[0041] In the upper left column of FIG. 6, the antenna of the satellite positioning device 6 is installed on the rooftop of a vehicle V, and is not blocked by a tunnel in a mountain M, and can receive positioning satellite signals from four or more positioning satellites S. Therefore, the satellite positioning device 6 sets the measurement reliability of the satellite positioning device 6 high based on the large number of satellites that can be captured. Then, the moving object speed estimation unit 82 calculates the measurement reliability coefficient C G (Furthermore, the measurement reliability coefficient C G ') is calculated large (step S7).

[0042] In the upper center section of FIG. 6, the antenna of the satellite positioning device 6 is installed on the rooftop of the vehicle V, and can receive positioning satellite signals from four or more positioning satellites S whose geometric arrangements are sufficiently varied. Therefore, the satellite positioning device 6 sets the measurement reliability of the satellite positioning device 6 high based on the fact that the DOP (Dilution Of Precision, the rate of decrease in positioning accuracy due to the geometric arrangement of the positioning satellites S; generally, the smaller the value, the higher the positioning accuracy) is. Then, the moving object speed estimation unit 82 sets the measurement reliability coefficient C G (Furthermore, the measurement reliability coefficient C G ') is calculated large (step S7).

[0043] In the upper right column of Fig. 6, the antenna of the satellite positioning device 6 is installed on the rooftop of a vehicle V, and is not blocked by nearby obstructions C or the like, and can receive positioning satellite signals with sufficient strength from four or more positioning satellites S. Therefore, the satellite positioning device 6 sets the measurement reliability of the satellite positioning device 6 high based on the fact that the radius E of the accuracy index (the accuracy of the positioning position is expressed by the radius of a circle, and the smaller the radius, the better the position accuracy) is small. Then, the moving body speed estimation unit 82 sets the measurement reliability coefficient C of the satellite positioning device 6 high. G (Furthermore, the measurement reliability coefficient C G ') is calculated large (step S7).

[0044] In addition, when "all" of the conditions in the upper left, upper middle, and upper right columns of FIG. 6 are satisfied, the measurement reliability of the satellite positioning device 6 is set high, and the measurement reliability coefficient C G (Furthermore, the measurement reliability coefficient C G It is desirable to calculate ') larger.

[0045] In the lower left column of FIG. 6, although the antenna of the satellite positioning device 6 is installed on the rooftop of the vehicle V, it is blocked by a tunnel in the mountain M and cannot receive positioning satellite signals from any of the positioning satellites S. Therefore, the satellite positioning device 6 sets the measurement reliability of the satellite positioning device 6 low based on the small number of satellites that can be captured. Then, the mobile object speed estimation unit 82 calculates the measurement reliability coefficient C G(Furthermore, the measurement reliability coefficient C G ') is calculated to be smaller (step S7).

[0046] In the lower center section of FIG. 6, the antenna of the satellite positioning device 6 is installed on the rooftop of the vehicle V, and although it is able to receive positioning satellite signals from four or more positioning satellites S, the geometric arrangement of the positioning satellites S is not sufficiently dispersed, resulting in a deterioration in positioning accuracy. Therefore, the satellite positioning device 6 sets the measurement reliability of the satellite positioning device 6 low based on the fact that the DOP (Dilution Of Precision, the rate at which positioning accuracy decreases due to the geometric arrangement of the positioning satellites S; generally, the smaller the value, the better the positioning accuracy). Then, the moving body speed estimation unit 82 sets the measurement reliability coefficient C G (Furthermore, the measurement reliability coefficient C G ') is calculated to be smaller (step S7).

[0047] In the lower right panel of Fig. 6, although the antenna of the satellite positioning device 6 is installed on the rooftop of the vehicle V, it is blocked by a nearby obstruction C, etc., and receives multipath signals from the positioning satellite S, resulting in a deterioration in positioning accuracy. Therefore, the satellite positioning device 6 sets the measurement reliability of the satellite positioning device 6 low based on the fact that the radius E of the accuracy index (the accuracy of the positioning position is expressed by the radius of a circle, and the smaller the radius, the better the position accuracy) is large. Then, the moving body speed estimation unit 82 sets the measurement reliability coefficient C of the satellite positioning device 6 low. G (Furthermore, the measurement reliability coefficient C G ') is calculated to be smaller (step S7).

[0048] In addition, when "any" of the conditions in the lower left column, the lower middle column, and the lower right column of FIG. 6 is satisfied, the measurement reliability of the satellite positioning device 6 is set low, and the measurement reliability coefficient C G (Furthermore, the measurement reliability coefficient C G It is desirable to calculate small '.

[0049] Therefore, depending on the influence of the external environment of the moving body, a weighting coefficient for the speed of the moving body measured by the satellite positioning device 6 can be calculated, and the weight of the speed of the moving body measured by the satellite positioning device 6 can be set among the current speeds of the moving body obtained by multiple types of speed measurement means that are weighted and added.

[0050] (Specific example of calculation process of measurement reliability coefficient of acceleration integral value disclosed herein) A specific example of the calculation process of the measurement reliability coefficient of the acceleration integral value of the present disclosure is shown in Fig. 7. The moving object speed estimation unit 82 calculates the measurement reliability coefficient C A (Furthermore, the measurement reliability coefficient C A Then, calculate whether to make it larger or smaller (step S8).

[0051] In the example of Fig. 7, when the moving body is stopped, the offset component of the acceleration a is estimated based on the fact that only the gravitational acceleration is applied to the moving body, and the acceleration a measured after removing the offset component from the acceleration a is integrated. Also, unlike Fig. 7, when the moving body is moving, the speed V of the moving body measured by the radar device 5 or the satellite positioning device 6 is R Or V G The offset component of the acceleration a may be estimated based on the above equation, and the acceleration a measured after removing the offset component from the acceleration a may be integrated.

[0052] When the time t in FIG. 7 is short, the current velocity V of the moving body is calculated from the time when the offset of the acceleration / angular velocity sensor 7 is removed (initial time 0, when the moving body is stopped or running). t The cumulative time t of the acceleration a of the moving object is short until the estimation time (current time t). Therefore, the time integral value ∫adt of the acceleration a of the moving object does not include much accumulated error due to the offset error of the acceleration / angular velocity sensor 7. Then, the moving object velocity estimation unit 82 estimates the measurement reliability coefficient C A (Furthermore, the measurement reliability coefficient C A ') is calculated large (step S8).

[0053] When the time t in FIG. 7 has passed for a long time, the current velocity V of the moving body is calculated from the time when the offset of the acceleration / angular velocity sensor 7 is removed (initial time 0, when the moving body is stopped or running). t The cumulative time t of the acceleration a of the moving object is long until the estimation time (current time t). Therefore, the time integral value ∫adt of the acceleration a of the moving object contains a large amount of cumulative error due to the offset error of the acceleration / angular velocity sensor 7. Then, the moving object velocity estimation unit 82 estimates the measurement reliability coefficient C A (Furthermore, the measurement reliability coefficient C A ') is calculated to be smaller (step S8).

[0054] Therefore, depending on the length of the acceleration accumulation time (regardless of the influence of the external environment of the moving body), a weighting coefficient of the time integral value of the acceleration of the moving body measured by the acceleration / angular velocity sensor 7 can be calculated, and a weight of the time integral value of the acceleration of the moving body measured by the acceleration / angular velocity sensor 7 can be set among the current velocities of the moving body obtained by multiple types of velocity measurement means that are weighted and added.

[0055] (Specific example of calculation process of multiple types of measurement reliability coefficients disclosed herein) FIG. 8 shows a specific example of a calculation process of the measurement reliability coefficient for the speed acquired by the radar device of the present disclosure, and the speed and acceleration integral value acquired by the satellite positioning device.

[0056] In the upper left, upper middle and upper right columns of FIG. 8, the moving object speed estimating unit 82 does not prioritize the radar device 5, the satellite positioning device 6 and the acceleration / angular velocity sensor 7, and the measurement reliability coefficient C R , the measurement reliability coefficient C of the satellite positioning device 6 G and the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 A The maximum possible values ​​are set to be equal for each of the above (steps S6 to S8).

[0057] In the lower left, lower center, and lower right columns of FIG. 8, the moving object speed estimation unit 82 estimates the measurement reliability coefficient C R , the measurement reliability coefficient C of the satellite positioning device 6G and the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 A The maximum possible values ​​are set to different values ​​for each (steps S6 to S8).

[0058] In the lower left, lower center, and lower right columns of FIG. 8, the moving object speed estimating unit 82 estimates the measurement reliability coefficient C R > Measurement reliability coefficient C of satellite positioning device 6 G > Measurement reliability coefficient C of acceleration / angular velocity sensor 7 A The maximum possible value increases in this order.

[0059] Unlike any of the cases in FIG. 8, the moving object speed estimating unit 82 determines the measurement reliability coefficient C of the acceleration / angular velocity sensor 7, taking into consideration that the estimation accuracy of the moving object speed is highest in the order of the acceleration / angular velocity sensor 7 > the satellite positioning device 6 > the radar device 5, etc. A > Measurement reliability coefficient C of satellite positioning device 6 G >Measurement reliability coefficient C of radar device 5 R The maximum possible value may be increased in this order.

[0060] In any case of FIG. 8, the moving object speed estimation unit 82 increases the measurement reliability coefficient C R (2) The higher / lower the measurement reliability of the satellite positioning device 6, the larger / smaller the measurement reliability coefficient C G (3) The shorter / longer the acceleration integration time after the offset of the acceleration / angular velocity sensor 7 is removed, the larger / smaller the measurement reliability coefficient C of the acceleration / angular velocity sensor 7 becomes. A is calculated to be larger / smaller (steps S6 to S8).

[0061] In this way, depending on the estimation accuracy of the speed of the moving body, it is not necessary to prioritize the radar device 5, the satellite positioning device 6, and the acceleration / angular velocity sensor 7, or the radar device 5, the satellite positioning device 6, and the acceleration / angular velocity sensor 7 may be prioritized, or the priorities may be in any order. [Industrial Applicability]

[0062] The moving object position estimation device and moving object position estimation program disclosed herein can estimate the current position of a moving object as long as the environment allows detection of targets that act as radar reflectors. [Explanation of symbols]

[0063] L1, L2: Mobile location estimation system V: Vehicle R: Road surface P:Snowfall S: Positioning satellite M:Mountains E: Radius of precision index C: Nearby obstructions 1: Satellite positioning device 2: Vehicle speed signal generator 3: Acceleration / Angular velocity sensor 4: Mobile object position estimation device 5: Radar equipment 6: Satellite positioning device 7: Acceleration / Angular velocity sensor 8: Mobile object position estimation device 41: Mobile data acquisition unit 42: Mobile object position estimation section 81: Mobile data acquisition unit 82: Moving object speed estimation section 83: Mobile object position estimation section

Claims

1. (1) a mobile body data acquisition unit that acquires, from a radar device mounted on the mobile body and measuring the speed of the mobile body, information on the speed of the mobile body and information on measurement reliability based on the received power and / or signal-to-noise ratio of the reflected wave of the radar device; (2) acquires, from a satellite positioning device mounted on the mobile body and measuring the positioning information of the mobile body, information on the speed of the mobile body and information on the measurement reliability of the satellite positioning device; (3) acquires information on the acceleration of the mobile body from an acceleration sensor mounted on the mobile body and measuring the acceleration of the mobile body; and (4) acquires information on the angular velocity of the mobile body from an angular velocity sensor mounted on the mobile body and measuring the angular velocity of the mobile body. (1) a measurement reliability coefficient of the radar device based on a measurement reliability based on a reception power and / or a signal-to-noise ratio of a reflected wave of the radar device, (2) a measurement reliability coefficient of the satellite positioning device based on the measurement reliability of the satellite positioning device, (3) a measurement reliability coefficient of the acceleration sensor based on an acceleration integration time of the acceleration sensor, and (4) a moving body speed estimation unit that weights and adds the time integral values ​​of the speed of the moving body measured by the radar device, the speed of the moving body measured by the satellite positioning device, and the acceleration of the moving body measured by the acceleration sensor using the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor as weighting coefficients; a moving object position estimating unit that estimates a current position of the moving object based on a time integral value of the velocity of the moving object estimated by the moving object velocity estimating unit through weighted addition, a time integral value of the angular velocity of the moving object measured by the angular velocity sensor, and a previously determined position of the moving object; A moving object position estimation device comprising:

2. The moving object speed estimation unit (1) calculates a measurement reliability coefficient of the radar device to be larger / smaller as the measurement reliability based on the reception power and / or S / N ratio of the reflected wave of the radar device is higher / lower, (2) calculates a measurement reliability coefficient of the satellite positioning device to be larger / smaller as the measurement reliability of the satellite positioning device is higher / lower, and (3) calculates a measurement reliability coefficient of the acceleration sensor to be larger / smaller as the acceleration integration time after offset removal of the acceleration sensor is shorter / longer.

2. The mobile object position estimation device according to claim 1 .

3. The moving object speed estimation unit recalculates the sum of the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor to a constant (including 1) and sets the result as the weighting coefficient.

3. The moving object position estimation device according to claim 1 or 2.

4. The moving object speed estimation unit (1) sets the maximum possible values ​​of the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor to equal values, or (2) sets the maximum possible values ​​of the measurement reliability coefficient of the radar device, the measurement reliability coefficient of the satellite positioning device, and the measurement reliability coefficient of the acceleration sensor to different values ​​according to the priority order of the radar device, the satellite positioning device, and the acceleration sensor.

3. The moving object position estimation device according to claim 1 or 2.

5. 2. A mobile object position estimation program for causing a computer to execute each processing step performed by each processing unit of the mobile object position estimation device according to claim 1.

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