CN112633703A - Air condition fusion precision evaluation system and method - Google Patents

Abstract

The invention belongs to the technical field of multi-source information fusion and evaluation, and discloses an empty condition fusion precision evaluation system and method, wherein the corresponding relation between space coordinate data and a timestamp is determined according to data stored in a reading protocol, the data is converted into longitude and latitude heights according to set sensor reference coordinates, the detection precision of each sensor is respectively calculated, the priority ranking of the sensors is obtained, the final reference precision is obtained according to a set evaluation method, the reference precision is used as an evaluation reference, the evaluation result of the empty condition fusion is calculated, and the final evaluation information and result are given; the invention can evaluate and identify the fusion precision of the air condition fusion system working in a simulation environment, a real-installation environment or a mixed environment by utilizing the evaluation algorithm of the proportion of the sensor detection data participating in fusion in each time-space domain and the final precision benchmark and the final fusion precision, and has good adaptability and reliability.

Description

Air condition fusion precision evaluation system and method

Technical Field

The invention belongs to the technical field of multi-source information fusion and evaluation, and particularly relates to an air condition fusion precision evaluation system and method suitable for multiple sensors and multiple targets in a complex environment.

Background

The air condition fusion system is one of the core components of the air defense command control system, is an important information source for battlefield situation judgment and combat decision, has important effects on battlefield perception, command decision, fire striking and the like of the command control system, and directly influences the viability of the air defense combat system in performance and efficiency. The precision index is a very important index of the air condition fusion system, and the precision index is the degree of the fusion track relative to the accuracy detected by the sensor after the fusion system carries out observation information extraction, tracking and comprehensive processing on the acquired target information, reflects the tracking capability and information guiding capability of the system, and is also an important basis for measuring the performance of the fusion algorithm. According to the information fusion theory, an excellent fusion algorithm can improve the accuracy of track information, but the battlefield environment is complex, the sensor is mainly influenced by radar, the uncertainty factors of the target detection process are many, such as electromagnetic interference, airflow disturbance, mountain land shielding, sensor detection characteristics and the like, the uncertainty and discontinuity of the detection data of the sensor can be caused by the factors, the fusion accuracy of the air fusion system is influenced, the difficulty of accuracy evaluation is increased, and how to determine the accuracy evaluation method and the reference is a problem which needs to be solved urgently.

Disclosure of Invention

In order to overcome the defects of the prior art, the invention provides an air condition fusion precision evaluation system and method, which aim at precision evaluation and identification of the air condition fusion system in a complex environment.

In order to achieve the purpose, the invention adopts the following technical scheme:

an air condition fusion precision evaluation system comprises a data input module, a data processing and precision evaluation module and an information display module, wherein the data input module is electrically connected with the data processing and precision evaluation module through a BLH data converter, and the output end of the data processing and precision evaluation module is electrically connected with the information display module through a cable; the data input module is electrically connected with the coordinate conversion module; the data end of the data processing and precision evaluation module is connected with the comprehensive evaluation module through a precision calculation module and a data analysis module to form a loop;

the data input module is a unified information input format module and configures the precision priority of the sensor; the data processing and precision evaluating module consists of a highest precision module, a lowest precision module, an average precision module and a self-adaptive weight module, and the information display module is used for outputting and displaying an evaluation result.

An empty fusion precision evaluation method comprises the steps of determining the corresponding relation between space coordinate data and a timestamp according to data stored in a reading protocol, converting the data into longitude and latitude heights according to set sensor reference coordinates, respectively calculating the detection precision of each sensor, obtaining sensor priority sequencing, obtaining final reference precision according to a set evaluation method, taking the reference precision as an evaluation reference, calculating an evaluation result of empty fusion, and giving final evaluation information and a result; the method comprises the following steps:

reading collected sensor information data and flight path truth value data; if the simulation data is the flight path true value data, the flight path true value data is original data generated by simulation; when the data is the data of the actual sensor, the true value data of the flight path is high-precision measurement data;

determining the corresponding relation between the space coordinate data and the time stamp according to the protocol format, calculating the detection precision of the sensor, and obtaining the priority sequence of the sensor;

protocol format: the method is used for realizing the data compatibility and the unification of the processing method, and defining the standard input protocol format; the data format comprises sensor data, flight path truth value data and fusion data;

the sensor data input format is: track batch number ID + reference coordinate system detection data (xData, yData, zData) + timestamp Time, wherein the track batch number is defined as the ID number of the same target, the reference coordinate system detection data is data of three axes of sensor detection acquired aiming at a sensor reference position, and the timestamp is the Time when a certain discrete data is acquired;

the flight path truth value data has two conditions, one is truth value data acquired by simulation, the other is target data acquired by high-precision detection equipment, and the recording format of the flight path truth value of the first condition is as follows: the method comprises the steps that track lot number ID + original data (B, L, H) + timestamp Time, wherein the original data are data of target simulation data in longitude B, latitude L and elevation H; the track truth value data format of the second case is the same as the sensor data format;

the recording format of the fused data is track batch number ID + original data (B, L, H) + timestamp Time;

thirdly, determining the reference precision: determining reference precision, calculating actual detection precision of the sensors, setting N sensors participating in fusion, and calculating detection precision sigma of each sensor according to sensor detection data_iThe calculation formula is as follows:

wherein x_ijThe detection data of the j point of the ith sensor,

is x_ijCorresponding track true value point data, wherein n is the track data quantity of the ith sensor; if the highest-precision evaluation method is selected, selecting the sensor with the highest precision as the reference precision; if the evaluation method with the lowest precision is selected, selecting the sensor with the lowest precision as the reference precision; if the average accuracy is selectedThe evaluation method selects the average accuracy of the sensors as the reference accuracy, i.e. sigma_w＝(∑σ_i) N; if the adaptive weight rule is selected, the calculation needs to be performed according to the following method:

1) according to the sensor detection precision sigma obtained by calculation_iThe sensors are sequenced from high to low to construct a sensor precision sequence R_i∈(R₁,R₂,…,R_N)；

2) Matching the sensor track association with a true value track; the method for utilizing the space distance in track association takes the minimum value of the space distance between the sensor track and the true track as the matching principle, and if the minimum value is calculated to obtain the sensor R_iThe spatial distance between the jth track and each true value track in the tracks is as follows:

D_j＝{d₁,d₂,…,d_k} (1)

wherein k is the batch number of the true flight path, and D is taken_jThe true track corresponding to the minimum value in (d) is associated with the jth sensor track, i.e., if d is_kIf the true value is the minimum, the kth true value track is correspondingly associated with the jth sensor track; in this way, the sensors R are sequentially found_iAll the tracks and the true value tracks are associated and matched with objects, and similarly, the tracks of all other sensors can determine the true value tracks which are associated and matched; a true value track is associated with multiple tracks in a sensor, and true value tracks j and sensors R are set_iIf n tracks are associated, the true track j is associated with the matched sensor R_iThe set of associated time domain intervals is:

wherein the content of the first and second substances,

indicating the sensor R_iThe time domain interval of the nth detection track,

is a sensor R_iThe start time of the nth detection track,

is a sensor R_iSetting the true value of the n-th detection track as K to obtain the sensor R_iThe set of associated time domain intervals is:

3) the matching method of the statistical fusion flight path and the true value flight path is the same as the step 2), and the time domain interval set of the true value flight path j associated to the m fusion flight paths is calculated as follows:

F_sj＝{[t₁₁,t₁₂],[t₂₁,t₂₂],…,[t_m1,t_m2]} (4)

then the total set of fusion track time domain intervals is:

F_s＝{F_s1,F_s2,…,F_sK} (5)

and if the total number of the fused tracks is M, the time cumulant of the fused tracks is as follows:

wherein, T_sjIs the fusion duration of the jth true track, an

L_jFor the number of fused tracks associated with the true track j, also set F_sjThe number of time domain intervals in (1); namely T_sIs F_sThe time period sum of all time domain intervals;

4) calculating the precision time cumulant T of each sensorⁱ；

5) Obtaining a sensor R_iPrecision weight value:

w_i＝Tⁱ/T_s (7)

if sigma w is caused by a calculation error_iNot equal to 1, then w needs to be adjusted_iCarrying out normalization processing again;

6) according to the formula σ_w＝∑w_iσ_iObtaining the reference accuracy sigma_w；

The calculation of the accumulated amount of the precision time of the sensor is a sub-process of acquiring the reference precision of the self-adaptive weight method, wherein the rest is fused with a time domain

The calculation is to divide the processed sensor time domain interval from the fusion time domain interval, wherein I is a fusion time domain complete set;

is to extract the sensor R which has acted in the fusion for the remaining period_iTime domain interval, then use

Calculating sensor R_iThe accumulated amount of accuracy time of (1) is:

wherein m isⁱIs a sensor R_iThe number of the tracks of (a) is,

is to utilize

Calculating sensor R_iThe calculation method of each track duration, namely the difference between the ending time and the starting time of the track time interval, is the same as the formula (6);

fourthly, an evaluation method: for a flight path, the information is determined by three coordinates, including three groups of data of longitude, latitude and elevation, which represent a flight path data, and then the flight path precision can also correspondingly obtain 3 valuesThus the final precision includes the fusion precision and the reference precision; the final precision would be a 3 value trade-off, then there would be σ_z＝(∑wσ_w) And/3, wherein w is determined by a scoring expert method according to the importance of three values, when 3 values are scored as a₁、a₂、a₃Then the three values of w are a₁/∑a_i、a₂/∑a_i、a₃/∑a_i(ii) a After the final precision is determined, determining a final evaluation result by comparing and fusing the final precision and the final reference precision; the evaluation method comprises a comparison method, a percentage scoring method and a satisfaction evaluation method,

1) the comparison method comprises the following steps: if the fusion precision is greater than the reference precision, judging that the fusion precision is unqualified, otherwise, judging that the fusion precision is qualified;

2) the percentage scoring method comprises the following steps: determining the percentage of the final fusion precision which is greater than or less than the final reference precision by taking the final reference precision as a standard, determining different percentage areas for scoring, wherein when the percentage is equal to 0, the percentage is 90, the percentage is 80 between 0 and 10 percent, and the percentage is 95 between 0 and-10 percent;

3) the satisfaction evaluation method comprises the following steps: using the formula f ═ exp (-0.1054 σ -_l/σ_w) Computing a final result, where σ_lTo fuse the final fusion precisions, σ_wThe final reference accuracy.

Due to the adoption of the technical scheme, the invention has the following advantages:

an air condition fusion precision evaluation system and method can evaluate and identify the fusion precision of the air condition fusion system working in a simulation environment, a real-installation environment or a mixed environment. The system is suitable for precision evaluation of a multi-sensor multi-target air condition fusion system in a complex environment, namely, the precision evaluation of the air condition fusion system in a simulation environment, a real-mounted environment or a mixed environment. Has good adaptability and reliability.

On the basis of analyzing the precision sequence of actual detection data of each sensor, the system calculates and obtains the reference precision by utilizing the proportion of the detection data of the sensors participating in fusion in each time-space domain, and the reference precision is used as the basis for evaluating the fusion precision. The method is an evaluation algorithm of final precision benchmark and final fusion precision, and can obtain an evaluation result of the air condition fusion precision.

Drawings

Fig. 1 is a block diagram of an air condition fusion precision evaluation system.

Detailed Description

As shown in fig. 1, an empty fusion precision evaluation system includes a data input module, a data processing and precision evaluation module, and an information display module, wherein the data input module is connected to the data processing and precision evaluation module through BLH data conversion, and an output end of the data processing and precision evaluation module is connected to the information display module; the data input module is connected with the coordinate conversion module; the data end of the data processing and precision evaluation module is connected with the comprehensive evaluation module through a precision calculation module and a data analysis module to form a loop;

the data input module is a unified information input format module and configures the precision priority of the sensor; the data processing and precision evaluating module consists of a highest precision module, a lowest precision module, an average precision module and a self-adaptive weight module, and the information display module is used for outputting and displaying an evaluation result.

An air condition fusion precision evaluation method is characterized in that collected sensor information data and flight path truth value data are read, and if the data are simulation data, the flight path truth value data are original data generated by simulation; if the data is the data of the real-mounted sensor, the true flight track data is high-precision measurement data, the corresponding relation between the space coordinate data and the time stamp is determined according to a design protocol format, the detection precision of the sensor is calculated, the priority ranking of the sensor is obtained, the reference precision is determined by four reference precision calculation methods, namely a highest precision method, a lowest precision method, an average precision method and an adaptive weight method, the precision index is evaluated by adopting a selected evaluation method, including a comparison method, an expert scoring method and a satisfaction evaluation method, and final evaluation information and results are given.

The method is characterized in that the weight precision of each sensor is quantitatively designed by reasonably measuring factors such as detection time, detection data measurement precision and the like aiming at the problem of inaccurate fusion track precision evaluation caused by uncertain time and space of multi-sensor track detection information, the air situation data is objectively and scientifically fused based on the reference precision of the evaluation fusion precision, and the performance of a fusion system and the fusion problem traceability are determined by the calculation and analysis of various evaluation methods of the system.

Protocol format: in order to realize data compatibility and uniform processing method, a standard input protocol format is defined. The data formats are mainly three, namely sensor data, track truth value data and fusion data.

The sensor data input format is: track batch number (ID) + reference coordinate system detection data (xData, yData, zData) + timestamp (Time), wherein the track batch number is defined as the ID number of the same target, the reference coordinate system detection data is the data of three axes of sensor detection acquired aiming at the reference position of the sensor, and the timestamp is the current Time for acquiring a certain discrete data.

The flight path truth value data has two conditions, one is truth value data acquired by simulation, the other is target data acquired by high-precision detection equipment, and the recording format of the flight path truth value of the first condition is as follows: track batch number (ID) + original data (B, L, H) + timestamp (Time), the original data being data of the target simulation data in longitude (B), latitude (L) and elevation (H); the second case has the same track truth data format as the sensor data format.

The format of the fused data record is track batch number (ID) + original data (B, L, H) + timestamp (Time).

And (3) determining the reference precision: to determine the reference accuracy, the actual detection accuracy of the sensor needs to be calculated. If N sensors participate in the fusion, the detection precision sigma of each sensor is calculated according to the detection data of the sensors_iThe calculation formula is as follows:

wherein x_ijThe detection data of the j point of the ith sensor,

is x_ijAnd n is the flight path data quantity of the ith sensor. If the highest-precision evaluation method is selected, selecting the sensor with the highest precision as the reference precision; if the evaluation method with the lowest precision is selected, selecting the sensor with the lowest precision as the reference precision; if the average accuracy evaluation method is selected, the average accuracy of the sensor is selected as the reference accuracy, namely sigma_w＝(∑σ_i) N; if the adaptive weight rule is selected, the calculation needs to be performed according to the following method:

1) according to the sensor detection precision sigma obtained by calculation_iThe sensors are sequenced from high to low to construct a sensor precision sequence R_i∈(R₁,R₂,…,R_N)；

2) And matching the sensor track association with the true track. The method of spatial distance available for track association takes the minimum value of the spatial distance between the sensor track and the true track as the matching principle, if the sensor R is obtained by calculation_iThe spatial distance between the jth track and each true value track in the tracks is as follows:

D_j＝{d₁,d₂,…,d_k} (9)

wherein k is the batch number of the true flight path, and D is taken_jThe true track corresponding to the minimum value in (d) is associated with the jth sensor track, i.e., if d is_kAnd if the absolute value is minimum, the kth true value track is correspondingly associated with the jth sensor track. In this way, the sensors R can be found out in turn_iAll tracks match the true track associations, and similarly, all other sensor tracks determine the true track associations. A true value track may be associated with multiple tracks in a sensor, setting true value track j to sensor R_iIf n tracks are associated, the true track j is associated with the matched sensor R_iThe set of associated time domain intervals is:

wherein the content of the first and second substances,

indicating the sensor R_iThe time domain interval of the nth detection track,

is a sensor R_iThe start time of the nth detection track,

is a sensor R_iSetting the true value of the n-th detection track as K to obtain the sensor R_iThe set of associated time domain intervals is:

3) the matching method of the statistical fusion track and the true value track is the same as 2), and the time domain interval set of the true value track j associated to the m fusion tracks can be calculated as follows:

F_sj＝{[t₁₁,t₁₂],[t₂₁,t₂₂],…,[t_m1,t_m2]} (12)

then the total set of fusion track time domain intervals is:

F_s＝{F_s1,F_s2,…,F_sK} (13)

and if the total number of the fused tracks is M, the time cumulant of the fused tracks is as follows:

wherein, T_sjIs the fusion duration of the jth true track, an

L_jFor the number of fused tracks associated with the true track j, also set F_sjThe number of time domain intervals in (1). It can be seen that T_sIs F_sThe time period sum of all time domain intervals;

4) calculating the precision time cumulant T of each sensorⁱ。

5) The sensor R can be obtained_iPrecision weight value:

w_i＝Tⁱ/T_s (15)

if sigma w is caused by a calculation error_iNot equal to 1, then w needs to be adjusted_iAnd carrying out normalization processing again.

6) According to the formula σ_w＝∑w_iσ_iObtaining the reference accuracy sigma_w。

The calculation of the accumulated amount of the precision time of the sensor is a sub-process of acquiring the reference precision of the self-adaptive weight method, wherein the rest is fused with a time domain

The calculation is to divide the processed sensor time domain interval from the fusion time domain interval, wherein I is a fusion time domain complete set;

is to extract the sensor R which has acted in the fusion for the remaining period_iTime domain interval, then use

Calculating sensor R_iThe accumulated amount of accuracy time of (1) is:

wherein m isⁱIs a sensor R_iThe number of the tracks of (a) is,

is to utilize

Calculating sensor R_iThe calculation method of each track duration, namely the difference between the ending time and the starting time of the track time interval, is the same as the formula (6).

The evaluation method comprises the following steps: for the information of a track, three groups of data such as longitude, latitude and elevation represent one track data, and the track precision also correspondingly obtains 3 values, so the final precision comprises fusion precision and reference precision; the final precision would be a 3 value trade-off, then there would be σ_z＝(∑wσ_w) [ 3 ] wherein w can be determined by a scoring expert method based on the importance of three values, e.g., 3 values are scored as a₁、a₂、a₃Then the three values of w are a₁/∑a_i、a₂/∑a_i、a₃/∑a_i. After the final precision is determined, a final evaluation result can be determined by comparing and fusing the final precision and the final reference precision, and the evaluation method comprises a comparison method, an expert scoring method and a satisfaction evaluation method, wherein the comparison method comprises the following steps: if the fusion precision is greater than the reference precision, judging that the fusion precision is unqualified, otherwise, judging that the fusion precision is qualified; the expert scoring method comprises the following steps: and determining the percentage of the final fusion precision greater than or less than the final reference precision by taking the final reference precision as a standard, and determining different percentage areas for scoring, for example: 90 at 0, 80 between 0 and 10%, 95 between 0 and-10%; the satisfaction evaluation method comprises the following steps: using the formula f ═ exp (-0.1054 σ -_l/σ_w) Computing a final result, where σ_lTo fuse the final fusion precisions, σ_wThe final reference accuracy.

The working process is as follows: the working process mainly comprises 3 parts, as shown in the figure, software reads data stored according to a protocol, converts the data into longitude and latitude heights according to set sensor reference coordinates, respectively calculates the precision of each sensor, obtains the final reference precision according to a set evaluation method, takes the reference precision as an evaluation reference, calculates the evaluation result of empty fusion, and outputs information for interface display.

Claims (2)

1. The utility model provides an empty condition fuses precision evaluation system which characterized in that: the system comprises a data input module, a data processing and precision evaluating module and an information display module, wherein the data input module is electrically connected with the data processing and precision evaluating module through a BLH data converter, and the output end of the data processing and precision evaluating module is electrically connected with the information display module through a cable; the data input module is electrically connected with the coordinate conversion module; the data end of the data processing and precision evaluation module is connected with the comprehensive evaluation module through a precision calculation module and a data analysis module to form a loop;

the data input module is a unified information input format module and configures the precision priority of the sensor; the data processing and precision evaluating module consists of a highest precision module, a lowest precision module, an average precision module and a self-adaptive weight module, and the information display module is used for outputting and displaying an evaluation result.

2. The assessment method of the air condition fusion precision assessment system according to claim 1, characterized in that: determining the corresponding relation between space coordinate data and a timestamp according to data stored by a reading protocol, converting the data into longitude and latitude heights according to set sensor reference coordinates, respectively calculating the detection precision of each sensor, obtaining the priority ranking of the sensors, obtaining the final reference precision according to a set evaluation method, taking the reference precision as an evaluation reference, calculating an evaluation result of air condition fusion, and giving final evaluation information and result; the method comprises the following steps:

reading collected sensor information data and flight path truth value data; if the simulation data is the flight path true value data, the flight path true value data is original data generated by simulation; when the data is the data of the actual sensor, the true value data of the flight path is high-precision measurement data;

determining the corresponding relation between the space coordinate data and the time stamp according to the protocol format, calculating the detection precision of the sensor, and obtaining the priority sequence of the sensor;

protocol format: the method is used for realizing the data compatibility and the unification of the processing method, and defining the standard input protocol format; the data format comprises sensor data, flight path truth value data and fusion data;

the sensor data input format is: track batch number ID + reference coordinate system detection data (xData, yData, zData) + timestamp Time, wherein the track batch number is defined as the ID number of the same target, the reference coordinate system detection data is data of three axes of sensor detection acquired aiming at a sensor reference position, and the timestamp is the Time when a certain discrete data is acquired;

the flight path truth value data has two conditions, one is truth value data acquired by simulation, the other is target data acquired by high-precision detection equipment, and the recording format of the flight path truth value of the first condition is as follows: the method comprises the steps that track lot number ID + original data (B, L, H) + timestamp Time, wherein the original data are data of target simulation data in longitude B, latitude L and elevation H; the track truth value data format of the second case is the same as the sensor data format;

the recording format of the fused data is track batch number ID + original data (B, L, H) + timestamp Time;

thirdly, determining the reference precision: determining reference precision, calculating actual detection precision of the sensors, setting N sensors participating in fusion, and calculating detection precision sigma of each sensor according to sensor detection data_iThe calculation formula is as follows:

wherein x_ijThe detection data of the j point of the ith sensor,

is x_ijCorresponding track true value point data, wherein n is the track data quantity of the ith sensor; if the highest-precision evaluation method is selected, selecting the sensor with the highest precision as the reference precision; if the evaluation method with the lowest precision is selected, selecting the sensor with the lowest precision as the reference precision; if the average accuracy evaluation method is selectedSelecting the average accuracy of the sensors as the reference accuracy, i.e. sigma_w＝(∑σ_i) N; if the adaptive weight rule is selected, the calculation needs to be performed according to the following method:

1) according to the sensor detection precision sigma obtained by calculation_iThe sensors are sequenced from high to low to construct a sensor precision sequence R_i∈(R₁,R₂,…,R_N)；

2) Matching the sensor track association with a true value track; the method for utilizing the space distance in track association takes the minimum value of the space distance between the sensor track and the true track as the matching principle, and if the minimum value is calculated to obtain the sensor R_iThe spatial distance between the jth track and each true value track in the tracks is as follows:

D_j＝{d₁,d₂,…,d_k} (1)

wherein k is the batch number of the true flight path, and D is taken_jThe true track corresponding to the minimum value in (d) is associated with the jth sensor track, i.e., if d is_kIf the true value is the minimum, the kth true value track is correspondingly associated with the jth sensor track; in this way, the sensors R are sequentially found_iAll the tracks and the true value tracks are associated and matched with objects, and similarly, the tracks of all other sensors can determine the true value tracks which are associated and matched; a true value track is associated with multiple tracks in a sensor, and true value tracks j and sensors R are set_iIf n tracks are associated, the true track j is associated with the matched sensor R_iThe set of associated time domain intervals is:

wherein the content of the first and second substances,

indicating the sensor R_iThe time domain interval of the nth detection track,

is a sensor R_iThe start time of the nth detection track,

is a sensor R_iSetting the true value of the n-th detection track as K to obtain the sensor R_iThe set of associated time domain intervals is:

3) the matching method of the statistical fusion flight path and the true value flight path is the same as the step 2), and the time domain interval set of the true value flight path j associated to the m fusion flight paths is calculated as follows:

F_sj＝{[t₁₁,t₁₂],[t₂₁,t₂₂],…,[t_m1,t_m2]} (4)

then the total set of fusion track time domain intervals is:

F_s＝{F_s1,F_s2,…,F_sK} (5)

and if the total number of the fused tracks is M, the time cumulant of the fused tracks is as follows:

wherein, T_sjIs the fusion duration of the jth true track, an

L_jFor the number of fused tracks associated with the true track j, also set F_sjThe number of time domain intervals in (1); namely T_sIs F_sThe time period sum of all time domain intervals;

4) calculating the precision time cumulant T of each sensorⁱ；

5) Obtaining a sensor R_iPrecision weight value:

w_i＝Tⁱ/T_s (7)

if sigma w is caused by a calculation error_iNot equal to 1, then w needs to be adjusted_iCarrying out normalization processing again;

6) according to the formula σ_w＝∑w_iσ_iObtaining the reference accuracy sigma_w；

The calculation of the accumulated amount of the precision time of the sensor is a sub-process of acquiring the reference precision of the self-adaptive weight method, wherein the rest is fused with a time domain

The calculation is to divide the processed sensor time domain interval from the fusion time domain interval, wherein I is a fusion time domain complete set;

is to extract the sensor R which has acted in the fusion for the remaining period_iTime domain interval, then use

Calculating sensor R_iThe accumulated amount of accuracy time of (1) is:

wherein m isⁱIs a sensor R_iThe number of the tracks of (a) is,

is to utilize

Calculating sensor R_iThe calculation method of each track duration, namely the difference between the ending time and the starting time of the track time interval, is the same as the formula (6);

fourthly, an evaluation method: the information about a flight path is composed of threeThree groups of data including longitude, latitude and elevation, which are determined by each coordinate, represent a flight path data, and the flight path precision also correspondingly obtains 3 values, so that the final precision comprises fusion precision and reference precision; the final precision would be a 3 value trade-off, then there would be σ_z＝(∑wσ_w) And/3, wherein w is determined by a scoring expert method according to the importance of three values, when 3 values are scored as a₁、a₂、a₃Then the three values of w are a₁/∑a_i、a₂/∑a_i、a₃/∑a_i(ii) a After the final precision is determined, determining a final evaluation result by comparing and fusing the final precision and the final reference precision; the evaluation method comprises a comparison method, a percentage scoring method and a satisfaction evaluation method;

1) the comparison method comprises the following steps: if the fusion precision is greater than the reference precision, judging that the fusion precision is unqualified, otherwise, judging that the fusion precision is qualified;

2) the percentage scoring method comprises the following steps: determining the percentage of the final fusion precision which is greater than or less than the final reference precision by taking the final reference precision as a standard, determining different percentage areas for scoring, wherein when the percentage is equal to 0, the percentage is 90, the percentage is 80 between 0 and 10 percent, and the percentage is 95 between 0 and-10 percent;

3) the satisfaction evaluation method comprises the following steps: using the formula f ═ exp (-0.1054 σ -_l/σ_w) Computing a final result, where σ_lTo fuse the final fusion precisions, σ_wThe final reference accuracy.

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