JPH07234131A - Method and apparatus for measuring state of moving element and state amount measuring system for the element - Google Patents

Abstract

PURPOSE:To improve stability and accuracy of measured data received from a measuring pot mounted at a moving element flying in the air and to reduce adverse influence of blanking. CONSTITUTION:Measured data 100 from two systems of measuring pots 2-1, 2-2 of an aircraft 1 are received, presence or absence of data error, etc., is checked by a communication malfunction unit 11, sorted according to items by a conversion sorter 12, and input to a rationalizing processor 14. The processor 14 decides rationality of data 101 according to items as to whether it falls within a predetermined threshold value or not. As a result, if both the two systems are effective, a mean value of the both is optimized. If only one system is effective, its value or a mean value with a complementary value is optimized. If the both are reactive, the complementary value is optimized. The complementary value is given from a control value setter 15, and decided according to the previous mean value or of an estimated value from a state estimating unit 21. Output data 103 of a physical amount is input to the unit 21 as an observed value.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a state quantity measuring device for a moving body such as an aircraft, and more particularly to a ground station for receiving transmission data from a plurality of measuring subsystems (measuring pods) mounted on the moving body. Regarding measurement method.

[0002]

2. Description of the Related Art A measurement pod mounted on an aircraft transmits the measured position, attitude angle, and the like by radio waves, and the ground station measures the state quantity of the aircraft and evaluates tactics. In this case, a radio wave bra-ranking area is generated in the shadow of the body of the measuring pod, which hinders data transmission to the ground station.

As a method for avoiding the influence of radio wave blanking, there is a method of selecting a measurement pod having a low radio wave blanking probability from a ground station, as described in Japanese Patent Laid-Open No. 5-155392.

That is, of the plurality of measurement pods equipped on the aircraft, the ground station estimates a pod having a high reception probability, and the ground station issues a data transmission command to the estimated pod. Send the measurement data to the ground. When there are multiple transmission pods, take the average for the same item of measurement data.

[0005]

However, according to the above-mentioned prior art, it is impossible to effectively select a measurement pod having a high reception probability from the ground when the aircraft is in high maneuvering motion (high acceleration motion). There are cases. There is also a problem that the data obtained from a plurality of measurement pods is not always effectively used.

It is an object of the present invention to optimize the measurement data for each item based on the data of a plurality of measurement subsystems (measurement pods) and improve the stability and accuracy of the data. To provide.

Another object of the present invention is to provide a method and apparatus for measuring the state of a moving body, which can ensure continuity of measurement data when effective data cannot be obtained by blanking.

Still another object of the present invention is to make it possible to use the measurement data of a plurality of pods mounted on a moving body as data of different specifications so that the state quantity of the moving body can be easily and accurately determined. It is to provide the required system.

[0009]

SUMMARY OF THE INVENTION An object of the present invention is to provide a method for measuring the state of a mobile unit, which receives measurement data of a plurality of measurement subsystems mounted on the mobile unit in time series,
This is achieved by performing a predetermined rationality determination of the measurement data received from the measurement subsystem of each system for each measurement item and optimizing the measurement data of the measurement item according to the determination result.

Further, the optimization of the measurement data is based on the result of the rationality judgment of the measurement data of the relevant measurement item, and when the measurement data of a plurality of systems are effective, only the average value thereof and the measurement data of one system are This is achieved by performing at least one of the data or the average value of the data and a predetermined complementary value when the data is valid, and the predetermined complementary value when the measurement data of the entire system is invalid.

Further, the plurality of measurement subsystems,
In a system including a state quantity measuring device that receives measurement data of a plurality of items from each of them in a time series on the ground side, the measurement subsystem is configured so that measurement data of the same item is transmitted from different positions on a moving body. The state quantity measuring device is arranged so as to be separated from each other so as to obtain specifications, and the state quantity measuring device inputs a measurement data of the same item from each measurement subsystem as another specification and calculates a predetermined state quantity of the moving body. It is achieved by providing.

[0012]

According to the method or apparatus for measuring a state of a moving body of the present invention, a rationality judgment for evaluating continuity of measurement data by a threshold value or the like, and a reception abnormality judgment for checking whether or not there is a reception abnormality in the measurement data are performed. Since the received data is optimized by the average value using all the valid data obtained as a result of these determinations, the stability is increased and it becomes possible to measure the moving body state quantity with high accuracy.

If, as a result of the above determination, no valid data is obtained for the measurement item, it is replaced by past data or its estimated value, that is, the previous average value or the estimated value by the Kalman filter, so that the blanking area, etc. The lack of measurement data due to can be complemented, and continuity of the physical state quantity of the moving body can be secured.

Further, according to the state quantity measuring system for a mobile body of the present invention, the measurement data of the same item from a plurality of measurement subsystems can be treated as different data items having different measurement positions, so that it is novel and high. It is possible to provide an accurate state quantity measuring method for a moving body.

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A first embodiment of the present invention will be described below with reference to FIGS.
Will be described in detail with reference to.

FIG. 2 is a conceptual diagram of an aircraft position evaluation system to which the moving body state measuring apparatus of the present invention is applied. In the present embodiment, the measurement subsystem (measuring instruments) equipped on the aircraft is configured in a pod format that is installed on both wings of the aircraft, and is referred to as a measurement pod in the following, but is not limited to this format. is not.

The aircraft 1 is equipped with two or more measurement pods 2 (this example will be described with two), and each pod 2 receives radio waves from four or more GPS satellites 3 to determine the absolute position of the aircraft. It is equipped with a GPS receiver for measurement. The measuring pod 2 is also equipped with an accelerometer and a gyro, and detects vector information such as acceleration and angular acceleration of the moving body.

The data detected by the measurement pod 2 is periodically polled from the ground station 4 to each pod of the aircraft and received in a time division manner. With respect to the received data, the calculation device 5 estimates the state quantities such as the position, wake and attitude of the aircraft, and the monitoring device 6 monitors the movement of the aircraft in real time.

FIG. 1 is a functional block diagram for explaining an embodiment of a moving body condition measuring apparatus. The transceiver front end 40 of the receiving station 4 is the measurement pod 2 of the system 2 of the aircraft 1.
-1, 2-2 receives physical quantities such as the position, velocity, acceleration, attitude angle, and angular acceleration of the aircraft, and event data related to predetermined operation information such as a weapon trigger. In this specification, these physical quantities and event data are collectively referred to as aircraft state quantities.

The calculation device 5 includes a measurement data processing section 10 for optimizing received data, a calculation section 20 including a state estimator 21 and an event data calculation section 22, and a track processing and a tactical evaluation based on the calculation results. Analysis display unit 30 for performing and displaying
Is equipped with.

The state estimator 21 has a Kalman filter for inputting the received position and posture angle as observed values and estimating the optimum values of the state quantities such as the position and posture angle of the moving body.
The Kalman filter also estimates the present or future state quantity by inputting the past state quantity. The event information calculation unit 22 has a function of performing a simulation of a predetermined operation based on the event data and outputting it to the analysis display unit 30.

The measurement data processing unit 10 receives the received data 10
A communication abnormality detecting unit 11 for detecting a communication abnormality of 0 and the received data 100 are converted into parallel data and classified into items S
/ P conversion / classification unit 12, communication system status register 13 for storing normal / abnormal status based on the detection result of communication abnormality detection unit 11, and data 10 for each item
1. The rationalization processing unit 14 that judges the rationality of 1 and performs rationalization processing on irrational data, and the control value setting unit 15 that sets a threshold value, a complementary value, or the like for the calculation of the rationalization processing unit 14.
It is composed by.

Communication abnormalities include transmitter / receiver abnormalities and transmission errors (timeout error, transmission word length error, CRC error, etc.). The abnormality of the transceiver is detected by the front end 40 and is notified to the communication abnormality detection unit 11. The transmission error is detected by the communication abnormality detection unit 11 based on the frame structure of received data, the parity check, and the like.

FIG. 3 shows a general frame structure of the received data 100. SYNC is an open flag and indicates the start of the basic unit. SA is a source address (measurement pod ID), DA is a destination address, L is a transmission word length, and F is a close flag indicating the end of the basic unit. CRC is an error detection bit and is used for detecting a data error.

FIG. 4 is a functional block showing a detailed structure of the rationalization processing unit 14. The data 101 of the two systems categorized for each item of the received data 100 is the validity determination unit 141.
On the basis of the threshold value 105 from the control value setting unit 15, if the physical quantity of the data is within the upper and lower limits of the threshold value 105, it is determined to be valid, and if not, the result is sent to the data selection control unit 142.

The data selection control unit 142 determines data to be selected based on the result of the validity determination unit 141 and the status data 102 from the communication system status register 13 and sends it to the data selection / switching unit 143. The data selection / switching unit 143 selects the data of the measurement pod determined by the data selection control unit 142 or the complementary value 106 from the control value setting unit 15 from the classified data 101, and the physical quantity 103 is the average. Value calculator 146
To the event data 104, the event data calculation unit 22
Transmit to.

The average value calculator 146 takes the average value of the physical quantity for each item and transmits it to the state estimator 21 which is composed of a Kalman filter. The threshold abnormality counting unit 144 counts the occurrence status of invalidity in the validity determination unit 141, and the communication abnormality counting unit 145 counts the occurrence status of communication abnormality, and sends them to the control value setting unit 15. The control value setting unit 15 changes the threshold value based on these data.

FIG. 5 is a functional block showing a detailed configuration of the control value setting unit 15. The previous value measured in the previous cycle is stored in the previous measurement value storage unit 151, and the state estimation value of the Kalman filter 21 is stored in the state estimation value storage unit 152 for each item. The estimated value by the Kalman filter 21 is
This value is estimated by inputting past (previous or previous) data.

The threshold and complementary value calculation unit 153 selects the data of the previous measured value storage unit 151 or the state estimated value storage unit 152 and outputs it as the complementary value 106 to the rationalization processing unit 14. The threshold value 105 includes storage units 151 and 152, an aircraft dynamic characteristic table 154, and a measurement sensor dynamic characteristic table 15.
5, the upper and lower limit values are determined and output from the respective data of the threshold abnormality counting unit 144 and the communication abnormality counting unit 145. In the aircraft dynamic characteristic table 154, constants are set according to the aircraft model. In the measurement sensor dynamic characteristic table 155, constants of dynamic characteristics of sensors such as a GPS receiver, a gyro, and an accelerometer are set.

As a method of setting the threshold value, for example, when the threshold abnormality count data or the communication abnormality count data becomes large, that is, when the threshold abnormality or the communication abnormality continues, the upper and lower limit widths of the threshold value are widened. Further, when the difference between the previous value and the Kalman filter state estimation value becomes large, the upper and lower limit widths are similarly widened.

FIG. 6 shows a calculation example in the average value calculation unit 146 using the state estimation value. At time t−1, both systems are within the threshold value (broken line), and the validity determination unit 141 determines that they are valid, and calculates the average value thereof. Time t and t + 1
Then, since one data exceeds the upper limit (broken line) and is determined to be invalid, the data of the system is estimated by the Kalman filter 21, and the average value of the estimated value and the valid data of the other system is obtained.

That is, at time t, the average value of the measured value D _2t of this time (t) and the estimated value D _{t / t-1} of time t at time t-1 is taken. At time t + 1, the average value of the observed value D _{1t + 1} and the estimated value D _{t + 1 / t} for time t + 1 at time t is obtained.

FIG. 7 is a flowchart showing the processing of the measurement data processing unit 10. First, the communication error detection unit 11
Then, the presence / absence of the transmitter / receiver of the measurement pods 2-1 and 2 and the presence or absence of an abnormality in the received data are detected, and the received data status 1
02 (normal / abnormal) is stored in the status register 13 (s101).

The rationalization processing unit 14 checks whether or not there is a communication abnormality regarding the data 101 classified by item (s
102), if there is no abnormality, the rationality is judged (s10).
3). The rationality determination is valid based on the threshold value given from the control value setting unit 15 if each data is within the range of the threshold value and invalid otherwise. According to this, even if there is no communication abnormality, even if the specific data continuously contains a large error due to the abnormality of the sensor in the measurement pod 2, it is invalidated, and the abnormal sensor is also detected.

The judgment of rationality basically monitors the continuity of data, and there are various methods other than the above.
For example, there is also a method of determining dynamic characteristics of data, such as discontinuity with a value estimated from past data. This can be realized by a method of validating if the rate of change of each data is within the threshold and invalidating otherwise.

The rationalization processing unit 14 performs data optimization processing according to the result of the rational judgment. First, if the data of both systems are valid, the average value is taken (s104). 1
If the system data is valid, it is set as the optimum data (s
105). If both systems are invalid, they are replaced by the complementary value given from the control value setting unit 15 and used as the optimum data. This complementary value is obtained in step s1 of the previous timing.
The optimum data (average value) obtained in 04 or the estimated value by the Kalman filter 21 is used.

Note that the communication abnormality data is invalid even if the rationality determination process is directly executed, so that step s102 can be omitted. Also, step s105
Then, the average value of the valid 1-system data and the complementary value may be output.

FIG. 8 shows the estimation by the Kalman filter.
The difference between the case of performing the conventional measurement data shown in FIG. 9A and the case of performing the optimum data by the rationalization processing unit 14 of the present embodiment shown in FIG.

In the conventional method, the Kalman filter 210 that minimizes the error outputs the optimum estimated value X based on the observed value Y detected by the sensor 300 such as GPS or gyro. In this case, the observed value Y is a position, a velocity, an acceleration, an angular acceleration, or the like, and includes an error having a property that it is white and its peak is not constant. On the other hand, the estimated value X is position, velocity, acceleration, attitude angle, angular velocity, angular acceleration, or the like.

The amplitudes of the Y and X graphs in the figure represent the deviation from the true value, and the larger the amplitude, the larger the error. That is, when the aircraft is in high maneuvering motion, the error of the output of the Kalman filter 210 becomes large in the conventional method.

On the other hand, in the method of this embodiment, the observation values Y (A) of the same measurement item from the two sensors 300A and 300B,
Y (B) is received, the observation value Y ′ optimized by the rationalization processing unit 14 is input, and the Kalman filter 210 outputs the optimum estimated value X ′.

As shown, the error from the sensor 300 is large as in the conventional case. However, due to the difference in the dynamic characteristics of the two sensors, the mutual errors are random and random. Therefore, by optimizing both by the rationalization process of the present embodiment, the error of the observed value Y ′ input to the Kalman filter 210 can be reduced.

According to this, the stability of the optimum estimated value X'by the Kalman filter is increased and the accuracy is improved. That is, in this embodiment, since the amplitude of the error of the observed value can be kept statistically constant, even if the amplitude of the error of 1 of the observed value becomes large, the estimated value is calculated by the time constant of the system dynamic characteristic that constitutes the filter. Since the error components are converged, the Kalman filter can maintain stable accuracy.

The above rational processing according to the present embodiment is performed when the received data is a physical quantity. Next, a rational process for event data of a plurality of measurement pods will be described.

FIG. 9 is a rationality judgment table of weapon launch data received from two measurement pods. As shown in the figure, in the case of firing a weapon, if one pod has a “present” signal, the determination is “yes”, and if two pods have a “no” signal, the determination is “no”. This criterion is determined according to the item of the event data, and contrary to the above, the determination may be “present” only when the two pods are “present”. Alternatively, it may follow a predetermined majority logic.

The determination table is provided in the control value setting unit 15 and the validity determination unit 141 confirms the validity. Alternatively, the data selection / switching unit 143 may be provided to directly determine the event data. As a result, the reliability of the event data can be improved even when a reception error occurs due to blanking or the like.

According to the present embodiment, the rationalization processing including the rationalization judgment and the data optimization is performed on the received data from the plurality of measurement pods, so that the reliability of the measured data is improved. In particular, when valid data cannot be obtained from the received data, the lack of data is complemented, so the position estimator 21 estimates the position and attitude of the aircraft, or the event data calculator 22 calculates the data. It can be processed continuously. This can improve the accuracy of wake analysis and tactical evaluation.

In the above-mentioned processing of FIG. 7, the rationality judgment is indispensable, but the invention is not limited to this. Figure 1
As shown in the flowchart of 0, the data optimization process may be performed immediately after the determination of the communication abnormality.

That is, when the second system is normal, the average value (s203), when only one system is normal, the normal system data (s204), and when the second system is communication abnormal, the above-mentioned complementary value (s205) is used. Output as optimum data. Note that in step s204, an average with the previous average value or the complementary value based on the Kalman filter estimated value may be calculated,
Alternatively, the normal value data may be compared with the complementary value, and if the difference is larger than a predetermined value, the complementary value may be adopted.

According to this, although the reliability of the data is reduced by the amount of the rationality judgment omitted, the continuity of the received data can be secured.

Next, a second embodiment of the present invention will be described with reference to FIGS. 11 and 12.

FIG. 11 is a diagram for explaining the principle of detecting the aircraft attitude angle according to this embodiment. FIG. 1A is a plan view of the aircraft, and FIG. 1B is a front view. The three measuring pods are arranged not on the same line of the aircraft, for example, below the wings P1 and P2 and below the fuselage P3. The interval between P1 and P2 is l ₁ , and the interval between P3 and P1 and P2 and the midpoint o is l ₂ .

In this case, when the absolute position Pi (ground coordinate system) of each pod is given, the attitude angle of the aircraft, for example, the roll angle φ is obtained as shown in FIG. That is, assuming that the pitch angle θ is 0, the roll angle φ can be obtained from (Equation 1).

[0054]

## EQU1 ## φ = sin ¹ ((z ₂ −z ₁ ) / l ₁ ) where Pi = (xi, yi, zi) i = 1, 2, 3 Similarly, one of the other corners is set to 0. Then, the pitch angle θ and the yaw angle ψ can be obtained.

FIG. 12 is a functional block diagram of the attitude angle measuring apparatus according to this embodiment. First, the absolute position measuring means 201
Up to 203, the absolute position converted into the ground coordinate system of each measurement pod is measured. Normally, these positions are the measurement pods 2.
It is obtained by the side and received by the ground station 4.

The three-axis angle calculation unit 205 determines the attitude angles φ ′, θ ′, ψ ′ based on the input absolute positions P1, P2, P3 and the constants of the intervals l ₁ , l ₂ from the set value table 206. To calculate. On the other hand, the vector detection means 204 by the gyro
The angular velocities Δφ, Δθ, and Δψ detected by are integrated by the integrator 207 to calculate the posture angles φ ″, θ ″, and ψ ″. The posture angles φ ′, θ ′, and ψ from these both means are calculated. 'And φ ”, θ”,
The optimal posture angles φ, θ, and ψ are estimated by the Kalman filter 208 using ψ ″ as an observation value.

Further, the posture angles φ, θ, ψ estimated by the adder 209 and the posture angles φ ″, θ ″, ψ ″ of the integrator 207 are calculated.
By taking the difference between, the drift of the output of the integrator 207 (accumulation of errors) can be easily corrected (reset) without resorting to a mathematical model.

According to the present embodiment, the position data of the three measurement pods are treated as separate data, and the attitude angle is easily obtained by calculation. Furthermore, the estimation accuracy of the Kalman filter is improved by using this attitude angle as an observed value in addition to that from the conventional gyro.

Further, the posture angle by the vector detecting means 204 is from one measurement pod,
If the posture angle from the measurement pod of the book is treated as the same data and the optimum value by the rationalization processing unit shown in the first embodiment is given to the integrator 207, the posture with further improved stability and accuracy can be obtained. The angle can be calculated.

The above is an example of estimating the attitude angle, but it is applicable to a physical quantity obtained from the measurement pod and given as an observation value of the Kalman filter. In this case, in many cases, the number of measurement pods to be treated as separate specifications may be two or more.

[0061]

According to the method of measuring the state of a moving body of the present invention, data of the same specifications from a plurality of measuring subsystems (measuring pods) mounted on the moving body are optimized by rational processing. In addition, the stability and accuracy of the measurement data can be improved, and the reliability of the state measuring device for the moving body can be improved.

Furthermore, the rationalization process can effectively compensate for the missing measurement data, so that the harmful effect of communication blanking can be reduced and the continuity of data can be maintained.

According to the state measuring system for a mobile body of the present invention, the data of the same measurement item can be treated as different data only by devising the arrangement of a plurality of measurement subsystems mounted on the mobile body. , It is possible to provide a highly accurate state quantity measuring system for a moving body with a new configuration.

[Brief description of drawings]

FIG. 1 is a functional block diagram showing an embodiment of a moving body state measuring apparatus of the present invention.

FIG. 2 is a conceptual diagram of an aircraft position evaluation system to which the present invention is applied.

FIG. 3 is a general frame configuration diagram of received data.

FIG. 4 is a functional block diagram of a rationalization processing unit.

FIG. 5 is a functional block diagram of a control value setting unit.

FIG. 6 is an explanatory diagram showing an example of average value processing.

FIG. 7 is a flowchart illustrating a processing operation of a measurement data processing unit.

FIG. 8 is an explanatory diagram illustrating an effect of rationalization processing.

FIG. 9 is a table showing an example of criteria for determining rationality of event data.

FIG. 10 is a flowchart illustrating an alternative processing operation of the measurement data processing unit.

FIG. 11 is a conceptual diagram illustrating a relationship between an aircraft attitude angle and a measurement pod position.

FIG. 12 is a functional block diagram of an attitude angle measuring device shown as an example of the state quantity measuring system for a moving body of the present invention.

[Explanation of symbols]

1 ... Aircraft, 2 ... Measurement pod (measurement subsystem), 3
... GPS satellite, 4 ... Ground station, 5 ... Calculation device, 6 ... Monitoring device, 10 ... Measurement data processing unit, 11 ... Communication error detection unit,
12 ... S / P conversion / classification unit, 13 ... Communication system status register, 14 ... Rationalization processing unit, 141 ... Effectiveness determination unit, 142 ... Data selection control unit, 143 ... Data selection /
Switching unit, 146 ... Average value calculation unit, 15 ... Control value setting unit,
151 ... Previously measured value storage unit, 152 ... State estimated value storage unit, 153 ... Threshold / complementary value calculation unit, 20 ... Calculation unit, 21
... State estimator, 208, 210 ... Kalman filter, 2
2 ... Event data calculation unit, 30 ... Analysis / display unit, 40
... Transceiver front end, 201 to 203 ... Absolute position measuring device, 204 ... Vector detecting means, 205 ... Three-axis angle calculating section, 207 ... Integrator.

Front page continuation (72) Inventor Yoshiro Sekiyama 5-2-1 Omika-cho, Hitachi-shi, Ibaraki Hitachi Ltd. Omika factory

Claims (13)

[Claims] 1. A method for measuring a state of a mobile body, which receives measurement data from a plurality of measurement subsystems mounted on a mobile body in a time series, wherein a predetermined measurement data received from the measurement subsystem of each system is provided. The method for measuring the state of a moving object, characterized by performing the rationality judgment of each measurement item and optimizing the measurement data of the measurement item according to the judgment result. 2. A method of measuring a state quantity of a mobile body, wherein measurement data from a plurality of measurement subsystems equipped on a mobile body flying in the air is received in time series on the ground side. A predetermined rationality judgment of the measurement data received from the system is performed for each measurement item, the measurement data of the measurement item is optimized according to the determination result, and the optimized plurality of related data are used as observation values for the mobile object. A method for measuring a state of a moving body, comprising estimating a predetermined state quantity of 3. The method of measuring a state of a moving body according to claim 1, wherein the predetermined rationality determination validates data having predetermined continuity when the measurement data is a physical quantity. . 4. The measurement data having the predetermined continuity according to claim 3, wherein the data or a change amount of the data is within a threshold value (limit value) set for each measurement item. Measuring method of moving body condition. 5. The optimization of the measurement data according to any one of claims 1 to 4, when the measurement data of a plurality of systems is valid according to a result of the rationality judgment of the measurement data of the measurement item. At least one of the average value and the average value of the data or the data and a predetermined complementary value when only the measurement data of the one system is valid and the predetermined complementary value when the measurement data of the entire system is invalid A method for measuring the state of a moving body, which is characterized in that 6. The state measurement of a moving body according to claim 5, wherein the predetermined supplemental value is an estimated value of the measurement item whose previous value is the average value or previous data. Method. 7. A method for measuring a state of a mobile body, wherein measurement data including event information is received on the ground side from measurement subsystems of a plurality of systems equipped on a mobile body flying in the air. Performing a predetermined rationality judgment of the event information received from the system according to a predetermined standard set for each measurement item, and converting the event information of the measurement item into data with or without depending on the judgment result. A method for measuring the state of a moving body, characterized by. 8. In order to receive measurement data of a plurality of measurement subsystems mounted on a moving body flying in the air,
In the condition measuring device of the moving body installed on the ground side, the receiving unit that receives the measurement data of multiple measurement items in time series and the validity of the received measurement data are determined, and the determination result for each measurement item A measurement data processing unit for optimizing data according to the above, and a state amount calculation unit for estimating a desired state amount based on the optimized data are provided, and the validity of the measurement data is determined. In order to achieve this, the measurement data processing unit is provided with communication abnormality determination means for determining the presence or absence of communication abnormality in the received measurement data and / or rationality determination means for determining the rationality of the received measurement data. Body condition measuring device. 9. The measurement data processing unit according to claim 8, wherein as a result of the determination by the reception abnormality determination unit or the rationality determination unit, when the measurement data of a plurality of systems is valid, an average value thereof is calculated, and/
Alternatively, the state measuring device for a mobile body is provided with an optimizing means for supplementing with an estimated value from the state amount calculation unit based on past data of the measurement item when the measurement data of the entire system is invalid. 10. Installed on the ground side to receive the measurement data of the position, acceleration, and angular acceleration of the moving body from a plurality of measurement subsystems of the system equipped on the moving body flying in the air. In a mobile state measuring device, a receiving unit that receives the measurement data of each item in time series, a communication abnormality determining unit that determines whether there is a communication abnormality in the received measurement data, and measurement data without communication abnormality Rationality determining means for determining rationality, and the result of the determination by the communication abnormality determining means and the rationality determining means, the average value when the measurement data of the measurement item is valid, or the measurement data of the entire system. Is invalid, a measurement data processing unit having an optimization unit that obtains a complementary value based on past data of the measurement item, and a data of each item optimized by the measurement data processing unit. A state measuring device for a mobile body, comprising: a Kalman filter for estimating the position of the mobile body using the data as an observation value; and a state quantity calculating unit for obtaining a track of the mobile body from the estimated position. 11. A plurality of measurement subsystems, which are mounted on a mobile body flying in the air and periodically sample measurement data indicating a physical quantity of movement, and measurement data of a plurality of items from each of the measurement subsystems. In a system including a state quantity measuring device that receives in time series on the side, the measurement subsystems are arranged separately so that measurement data of the same item can be obtained as different data from different positions on the mobile body. The state quantity measuring device is characterized in that the state quantity measuring device is provided with an arithmetic unit for inputting measurement data of predetermined items from each measurement subsystem as separate data items to obtain a predetermined state quantity of the moving body. Measuring system. 12. The measurement unit according to claim 11, wherein the measurement data is provided with three measurement subsystems for sampling an absolute position of a moving body, and the calculation unit for obtaining a posture angle of the moving body as the state quantity, Three-axis angle calculation means for calculating the first attitude angle of the moving body by inputting the absolute position from each measurement subsystem as different specifications, and the angular velocity from one or more of the measurement subsystems as the same specifications. And a Kalman filter for estimating the optimum posture angle of the moving body by using the posture angle from the three-axis angle calculating means and the integrating means as an observation value. Measuring system for state quantity of moving body. 13. The state quantity measuring device according to claim 11, performs rationality determination of angular velocities received from each of the measurement subsystems as the same specifications, and optimizes data according to the determination result. A state quantity measuring system for a mobile body, comprising a measurement data processing unit for performing.