Data fusion processing method for frequency usage behavior description based on adaptive reachable density

Abstract

The application provides a data fusion processing method for frequency use behavior description based on adaptive reachable density, signal frequency parameters, signal statistical spectrum, signal communication parameters and signal direction degree are calculated through intermediate frequency spectrum, IQ and measurement data in spectrum monitoring; parameter measurement results of single sensing position and single measurement are formed by reorganizing signal frequency parameters, signal statistical spectrum, signal communication parameters and signal direction degree based on sensing position, collection time and collection frequency; signal parameters of single sensing position and single measurement are extracted from the parameter measurement results, signal parameters are classified and normalized through adaptive reachable density clustering, and normalized results of signal parameters of single sensing position and at least twice measurement are formed; signal parameter fusion is performed on each electromagnetic target based on the normalized results of signal parameters of single sensing position and at least twice measurement and corresponding electromagnetic targets. The problem that monitoring results of multiple measurements and multiple sensing positions cannot be fused is solved.

Description

Technical Field

[0002] This invention relates to the technical field of electromagnetic spectrum management, and specifically to a method for fusion processing of frequency behavior description data based on adaptive reachability density. Background Technology

[0004] Electromagnetic spectrum monitoring refers to the measurement of the spectral characteristic parameters of electromagnetic signals in the air using monitoring equipment and technical means. It is a fundamental method for understanding and mastering the use of the electromagnetic spectrum. Existing technologies use intermediate frequency spectrum, IQ, and direction-finding data collected from individual sensing locations to calculate signal spectral parameters, communication parameters, directionality, and other information to describe the signal parameters around each sensing location.

[0005] However, in real-world environments, due to factors such as transmission distance and multipath effects, the signal data collected from different receiving locations varies greatly. The method of acquiring signal parameters by collecting intermediate frequency spectrum, IQ, and direction-finding data from a single sensing location for a short period of time can only reflect the frequency usage behavior of electromagnetic targets at a single point over a short period of time, and cannot meet the practical needs of mastering the frequency usage parameters of electromagnetic targets. Summary of the Invention

[0007] To address the problems existing in the prior art, this invention provides a data fusion processing method for frequency behavior description based on adaptive reachability density. This method solves the technical problem that existing technologies suffer from significant differences in signal data collected from different receiving locations due to factors such as transmission distance and multipath effects. The method of acquiring signal parameters by collecting intermediate frequency spectrum, IQ, and direction-finding data from a single sensing location for a short period of time can only reflect the frequency behavior of electromagnetic targets at a single point for a short time, and cannot meet the practical needs of mastering the frequency parameters of electromagnetic targets.

[0008] This invention provides a data fusion processing method for frequency behavior description based on adaptive reachability density, comprising:

[0009] S1. Extract the intermediate frequency spectrum, IQ and measurement data from the spectrum monitoring, and calculate the signal frequency parameters, signal statistical spectrum, signal communication parameters and signal directionality based on the intermediate frequency spectrum, IQ and measurement data respectively;

[0010] S2. Based on the sensing location, acquisition time, and acquisition frequency, the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality are compiled to form the parameter measurement results of a single measurement at a single sensing location.

[0011] S3. Extract the signal parameters of a single measurement at a single sensing location from the parameter measurement results, and classify and normalize the signal parameters by adaptive reachability density clustering to form a normalized result of signal parameters of at least two measurements at a single sensing location.

[0012] S4. Based on the normalized results of the signal parameters measured at least twice at the single sensing position, and by associating them with the corresponding electromagnetic targets through adaptive reachability density clustering, signal parameter fusion is achieved for each electromagnetic target.

[0013] Optionally, the step of extracting the intermediate frequency spectrum, IQ, and measurement data from the spectrum monitoring, and calculating the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality based on the intermediate frequency spectrum, IQ, and measurement data, respectively, includes:

[0014] S101. Based on the intermediate frequency data, calculate the frequency of a single measurement at a single sensing location. ,bandwidth Field strength and their corresponding root mean square errors , , , is represented as:

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[0016]

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[0018]

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[0021] Among them, frequency For the frequency of each frame, For the bandwidth of each frame and The field strength for each frame. The frame number;

[0022] S102. Based on the intermediate frequency data, calculate the signal statistical spectrum, and express the maximum, minimum, and average field strengths as follows:

[0023]

[0024]

[0025]

[0026] in, Sampling time, For frequency, This is the field strength value. This is the sampling time sequence number. This is the frequency sequence number.

[0027] Optionally, the step of extracting the intermediate frequency spectrum, IQ, and measurement data from the spectrum monitoring, and calculating the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality based on the intermediate frequency spectrum, IQ, and measurement data, further includes:

[0028] S103. Based on the IQ data, extract the modulation method, communication system, and confidence level of the signal;

[0029] S104, Based on the measurement data The root mean square error of the extracted signal orientation and the corresponding signal orientation are statistically analyzed and expressed as follows:

[0030]

[0031]

[0032] in, For signal directionality, For frame number, This is the root mean square error.

[0033] Optionally, the step of compiling the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality based on the sensing location, acquisition time, and acquisition frequency to form the parameter measurement results for a single measurement at a single sensing location includes:

[0034] The intermediate frequency spectrum, IQ, and the acquisition location, acquisition frequency, and acquisition time of the measurement data are obtained. Signal data with the same acquisition time, acquisition frequency, and acquisition location are compiled to form the parameter measurement result of a single measurement at a single sensing location.

[0035] Optionally, the signal parameters from a single measurement at a single sensing location are extracted from the parameter measurement results. These signal parameters are then classified and normalized using adaptive reachability density clustering to form a normalized result of signal parameters from at least two measurements at a single sensing location, including:

[0036] S301. Extract the first frequency from the parameter measurement results. First bandwidth The first strong First dimension , and their corresponding root mean square errors , , , ,in To sense the location sequence number, This refers to the sequence number of the signal parameter in a single measurement.

[0037] S302. Select any sensing location and follow the sequence number of the signal parameters measured in a single measurement. The signal parameters extracted pairwise in the direction are and ,in ;

[0038] S303, Extract signal parameters from each pair of signals. and Adaptive reachability density temporal clustering, judgment and Whether the distance between the signal parameters and the corresponding root mean square error is less than 3 times is expressed as follows:

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[0040]

[0041]

[0042]

[0043] If it meets the criteria, it is classified as one category; otherwise, it is not.

[0044] S304. Repeat steps S302-S303 until all signal parameters at all sensing locations have been clustered pairwise to obtain the time dimension clusters. ,in, For time dimension category number, The sequence number of the signal parameter contained in the time dimension class;

[0045] S305. The signal parameters in the time dimension class are fused and represented as follows:

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[0053] .

[0054] Optionally, the step of fusing signal parameters for each electromagnetic target based on the normalized results of at least two measurements at the single sensing location, and associating them with the corresponding electromagnetic targets through adaptive reachability density clustering, includes:

[0055] S401. Extract the second frequency from the signal parameters of at least two signals at the single sensing position. Second bandwidth The second strong Second dimension , and their corresponding root mean square errors , , , ,in For monitoring location serial number, The time dimension class number;

[0056] S402, along Extract signal parameters pairwise in the direction, with the sequence number as follows: and ,in ;

[0057] S403, Extract signal parameters from each pair of signals. and Adaptive reachable density temporal clustering to extract signal parameters. and The second frequency, second bandwidth, and second field strength are defined, and their distances are determined to be less than three times the corresponding root mean square error, as expressed in the following:

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[0059]

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[0061] If it meets the criteria, it is classified as one category; otherwise, it is not.

[0062] S404. Repeat steps S402-S403 until all sensing locations have completed pairwise clustering of signal measurement parameters from at least two separate measurements, thus obtaining the spatial dimension classes. ,in For time dimension category number, This refers to the index of the signal parameters contained in the class. The time dimension class number;

[0063] S405, Regarding spatial dimension classes The model parameters in the data are combined and represented as follows:

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[0070] S406. Using a positioning algorithm, analyze the fused orientation and its corresponding root mean square error. The electromagnetic target position is obtained by fusion.

[0071] Compared with the prior art, the present invention:

[0072] 1. By compiling the collected measurement signal parameters, the problem that signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality cannot be directly correlated when obtained from different data files is solved.

[0073] 2. By using the adaptive reachability density clustering method, the problem of the inability to fuse monitoring results from multiple measurements and multiple sensing locations was solved, realizing the fusion of electromagnetic target frequency usage behavior description data. This has promoted the advancement of electromagnetic target frequency usage behavior description data from describing measurement data at a single location at a certain time to describing electromagnetic target frequency usage behavior. Attached Figure Description

[0075] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0076] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0077] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0078] Figure 2 This is a schematic diagram of signal spectrum parameter extraction according to the present invention;

[0079] Figure 3This is a schematic diagram of signal statistical spectrum extraction according to the present invention;

[0080] Figure 4 This is a schematic diagram of signal direction finding parameter extraction according to the present invention;

[0081] Figure 5 This is a schematic diagram of the signal parameter compilation of the present invention;

[0082] Figure 6 This is a schematic diagram of the time fusion calculation of signal measurement parameters based on adaptive reachability density according to the present invention;

[0083] Figure 7 This is a schematic diagram of the spatial fusion calculation of electromagnetic target frequency parameters based on adaptive reachability density according to the present invention;

[0084] Figure 8 This is a schematic diagram of the electromagnetic target positioning information fusion calculation of the present invention. Detailed Implementation

[0086] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other implementation cases obtained by those skilled in the art without creative effort are within the scope of protection of this application. Functional units with the same reference numerals in the examples of this invention have the same and similar structures and functions.

[0087] See Figure 1 This invention provides a data fusion processing method for frequency behavior description based on adaptive reachability density, comprising:

[0088] S1. Extract the intermediate frequency spectrum, IQ and measurement data from the spectrum monitoring, and calculate the signal frequency parameters, signal statistical spectrum, signal communication parameters and signal directionality based on the intermediate frequency spectrum, IQ and measurement data respectively;

[0089] S2. Based on the sensing location, acquisition time, and acquisition frequency, the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality are compiled to form the parameter measurement results of a single measurement at a single sensing location.

[0090] S3. Extract the signal parameters of a single measurement at a single sensing location from the parameter measurement results, and classify and normalize the signal parameters by adaptive reachability density clustering to form a normalized result of signal parameters of at least two measurements at a single sensing location.

[0091] S4. Based on the normalized results of the signal parameters measured at least twice at the single sensing position, and by associating them with the corresponding electromagnetic targets through adaptive reachability density clustering, signal parameter fusion is achieved for each electromagnetic target.

[0092] In this embodiment, S1, the intermediate frequency spectrum, IQ and measurement data are extracted from the spectrum monitoring, and the signal frequency parameters, signal statistical spectrum, signal communication parameters and signal directionality are calculated based on the intermediate frequency spectrum, IQ and measurement data.

[0093] See Figure 2 For the intermediate frequency spectrum data in a single measurement at a single sensing location, the frequency of each frame in the intermediate frequency spectrum data is obtained. ,bandwidth Field strength and their corresponding root mean square errors , , , is represented as:

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[0100] Among them, frequency For the frequency of each frame, For the bandwidth of each frame and The field strength for each frame. This is the frame number.

[0101] Then, the signal statistical spectrum is extracted to characterize the maximum / minimum / mean spectrum of the signal within a certain geographical location and time period, specifically:

[0102] See Figure 3 For intermediate frequency spectrum data acquired in a single acquisition at a single sensing location, calculate the statistical spectrum of the signal within a certain time period, including the sampling time. ,frequency Field strength value ,in This is the sampling time sequence number. The frequency index is used; the maximum, minimum, and average field strengths of the signal are expressed as follows:

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[0106] Next, signal communication parameters are extracted to characterize the signal modulation scheme, communication system, and confidence level at a specific geographical location and time period. For IQ data collected in a single instance from a single sensing location, the signal modulation scheme, communication system, and confidence level are extracted according to ITU-R Recommendation SM.1600.

[0107] Finally, see Figure 4 Signal direction finding / positioning extraction is performed to characterize the signal direction finding / positioning results and fluctuation range for a specific geographic location and time period. For direction finding / positioning data collected from a single sensing location in a single transaction, the signal direction finding and positioning position, as well as the corresponding root mean square error (RMSE), are statistically extracted. The positioning position is the intersection position of the direction finding fusion results from multiple sensing locations.

[0108] Since the direction finding data of a single-sensor location measurement is generally obtained from multiple frames of measurements, including direction indication, the signal is typically obtained from a single measurement. ,in The frame number is used to statistically calculate the signal direction-finding parameters of a single measurement at a single sensing location, and to calculate the signal orientation. and the corresponding root mean square error , is represented as:

[0109]

[0110] .

[0111] S2. Based on the sensing location, acquisition time, and acquisition frequency, the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality are compiled to form the parameter measurement results of a single measurement at a single sensing location.

[0112] This step is used to compile the measured signal parameters, representing the signal frequency, bandwidth, field strength, direction finding / positioning, modulation method, and communication system at a specific geographical location and time period. Based on step S1, the intermediate frequency spectrum, IQ, and direction finding / positioning data are typically acquired at different times and stored in three separate files. In actual processing, these data need to be compiled according to rules to form a complete information table describing the signal parameters.

[0113] See Figure 5 Based on the intermediate frequency spectrum, IQ, and the location (longitude) of the direction finding / positioning data acquisition location. ,latitude ab sampling frequency Collection time The results of step 1 are then compiled; when the three files... , , same, The signal processing results within one day are compiled into a complete information table, with the acquisition time... The time can be customized according to requirements.

[0114] S3. Extract the signal parameters of a single measurement at a single sensing location from the parameter measurement results, and classify and normalize the signal parameters by adaptive reachability density clustering to form a normalized result of signal parameters of at least two measurements at a single sensing location.

[0115] Step S3 primarily involves the temporal fusion of measured signal parameters, used to characterize the normalized fusion results of signal frequency, bandwidth, field strength, directionality / positioning, modulation scheme, communication system, and latency from previous measurements at a specific geographical location. See also... Figure 6 Based on the signal parameters in step S2, the signal parameters of each single measurement at each sensing location are extracted pairwise, specifically as follows:

[0116] Extract the first frequency from the parameter measurement results. First bandwidth The first strong First dimension , and their corresponding root mean square errors , , , ,in To sense the location sequence number, This refers to the sequence number of the signal parameter in a single measurement.

[0117] Select a sensing location and follow the sequence number of the signal parameters measured in a single measurement. The signal parameters extracted pairwise in the direction are and ,in ;

[0118] Then, extract the signal parameters pairwise. and Adaptive reachability density temporal clustering is performed. Two extracted signal parameters whose distance is less than three times their corresponding root mean square error are grouped into one class, which can be represented as:

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[0123] Conversely, they are not classified into the same category.

[0124] Then, extract two more signal parameters and repeat the above process until all signal parameters at a certain sensing location are clustered in time pairwise.

[0125] Repeat the above process at different sensing locations until all signal parameters at all sensing locations have undergone temporal clustering. This yields the temporal dimension classes. ,in For time dimension category number, This refers to the index of the signal parameter contained in the time dimension class.

[0126] Finally, the measurement signal parameters contained in the class are fused, where

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[0135] S4. Based on the normalized results of at least two measurements of signal parameters at the single sensing position, associate them with the corresponding electromagnetic targets, and perform signal parameter fusion for each electromagnetic target.

[0136] Step S4 mainly realizes the spatial fusion of frequency parameters of electromagnetic targets, which is used to characterize the normalized fusion results of frequency, bandwidth, field strength, modulation method, communication system, etc. of previous measurements of electromagnetic targets. First, refer to Figure 7 The signal parameters from each sensing location's previous measurements are extracted pairwise. The signal parameters extracted in step 3 include the second frequency. Second bandwidth The second strong Second dimension and the corresponding root mean square error , , , ,in For monitoring location serial number, This is the time dimension class number. Along Extract signal parameters pairwise in the direction, with the sequence number as follows: and ,in .

[0137] Secondly, extract signal parameters pairwise. and Perform adaptive reachability density temporal clustering. Extract the parameters from the two sets of signals. , , The root mean square error corresponding to distances less than 3 times is classified into one class, which can be represented as:

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[0141] Conversely, they are not classified into the same category.

[0142] Next, two signal parameters are extracted, and the above process is repeated until the pairwise measurements of signal parameters at each sensing location are complete, thus achieving spatial fusion of electromagnetic target frequency parameters. This leads to the acquisition of spatial dimension classes. ,in For time dimension category number, This refers to the index of the signal parameters contained in the class. This is the time dimension class number.

[0143] Finally, the measurement signal parameters contained in the class , , To merge, where:

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[0150] See Figure 8 Then, the orientation is determined by the positioning algorithm. Root mean square error of orientation The electromagnetic target position is obtained by fusion, thus obtaining the electromagnetic target location. , .

[0151] This invention solves the problem that signal spectrum parameters, signal statistical spectrum, signal communication parameters, and signal directionality cannot be directly correlated when obtained from different data files by compiling signal measurement parameters; it also provides an adaptive reachability density clustering method to solve the problem that monitoring results from multiple measurements and multiple sensing locations cannot be fused, and realizes the fusion of electromagnetic target frequency behavior description data, thus promoting the advancement of electromagnetic target frequency behavior description data from describing measurement data at a single location at a certain time to describing electromagnetic target frequency behavior.

[0152] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0153] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A data fusion processing method for frequency behavior description based on adaptive reachability density, characterized in that, include: S1. Extract the intermediate frequency spectrum, IQ and measurement data from the spectrum monitoring, and calculate the signal frequency parameters, signal statistical spectrum, signal communication parameters and signal directionality based on the intermediate frequency spectrum, IQ and measurement data respectively; S2. Based on the sensing location, acquisition time, and acquisition frequency, the signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality are compiled to form the parameter measurement results of a single measurement at a single sensing location. S3. Extract the signal parameters of a single measurement at a single sensing location from the parameter measurement results, and classify and normalize the signal parameters by adaptive reachability density clustering to form a normalized result of signal parameters of at least two measurements at a single sensing location. S4. Based on the normalized results of at least two measurements of signal parameters at the single sensing position, and by associating them with the corresponding electromagnetic targets through adaptive reachability density clustering, signal parameter fusion is achieved for each electromagnetic target.

2. The data fusion processing method for frequency behavior description based on adaptive reachability density as described in claim 1, characterized in that, The extraction of intermediate frequency (IF) spectrum, IQ, and measurement data from spectrum monitoring, and the calculation of signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality based on the IF spectrum, IQ, and measurement data, respectively, include: S101. Based on the intermediate frequency data, calculate the frequency of a single measurement at a single sensing location. ,bandwidth Field strength and their corresponding root mean square errors , , , is represented as: Among them, frequency For the frequency of each frame, For the bandwidth of each frame and The field strength for each frame. The frame number; S102. Based on the intermediate frequency data, calculate the statistical spectrum of the signal, and express the maximum, minimum, and average field strengths as follows: in, Sampling time, For frequency, This is the field strength value. This is the sampling time sequence number. This is the frequency sequence number.

3. The data fusion processing method for frequency behavior description based on adaptive reachability density as described in claim 2, characterized in that, The process of extracting the intermediate frequency spectrum, IQ, and measurement data from spectrum monitoring, and calculating signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality based on the intermediate frequency spectrum, IQ, and measurement data, also includes: S103. Based on the IQ data, extract the modulation method, communication system, and confidence level of the signal; S104, Based on the measurement data The root mean square error of the extracted signal orientation and the corresponding signal orientation are statistically analyzed and expressed as follows: in, For signal directionality, For frame number, This is the root mean square error.

4. The data fusion processing method for frequency behavior description based on adaptive reachability density as described in claim 3, characterized in that, The signal frequency parameters, signal statistical spectrum, signal communication parameters, and signal directionality are compiled based on the sensing location, acquisition time, and acquisition frequency to form the parameter measurement results of a single measurement at a single sensing location, including: The intermediate frequency spectrum, IQ, and measurement data acquisition location, acquisition frequency, and acquisition time are obtained. Signal data with the same acquisition time, acquisition frequency, and acquisition location are compiled to form the parameter measurement results of a single measurement at a single sensing location.

5. The data fusion processing method for frequency behavior description based on adaptive reachability density as described in claim 4, characterized in that, The signal parameters from a single measurement at a single sensing location are extracted from the parameter measurement results. These parameters are then classified and normalized using adaptive reachability density clustering to form a normalized result for signal parameters from at least two measurements at a single sensing location, including: S301. Extract the first frequency from the parameter measurement results. First bandwidth The first strong First dimension , and their corresponding root mean square errors , , , ,in To sense the location sequence number. This refers to the sequence number of the signal parameter in a single measurement. S302. Select any sensing location and follow the sequence number of the signal parameters measured in a single measurement. The signal parameters extracted pairwise in the direction are and ,in ; S303, Extract signal parameters from each pair of signals. and Adaptive reachability density temporal clustering, judgment and Whether the distance between the signal parameters and the corresponding root mean square error is less than 3 times is expressed as follows: If it meets the criteria, it is classified as one category; otherwise, it is not. S304. Repeat steps S302-S303 until all signal parameters at all sensing locations have been clustered pairwise to obtain the time dimension clusters. ,in, For time dimension category number, The sequence number of the signal parameter contained in the time dimension class; S305. The signal parameters in the time dimension class are fused and represented as follows: 。 6. The data fusion processing method for frequency behavior description based on adaptive reachability density as described in claim 5, characterized in that, The process of normalizing signal parameters based on at least two measurements at the single sensing location, and associating them with corresponding electromagnetic targets through adaptive reachability density clustering, to achieve signal parameter fusion for each electromagnetic target includes: S401. Extract the second frequency from the signal parameters of at least two signals at the single sensing position. Second bandwidth The second strong Second dimension , and their corresponding root mean square errors , , , ,in For monitoring location serial number, For time dimension class index; S402, along Extract signal parameters pairwise in the direction, with the sequence number as follows: and ,in ; S403, Extract signal parameters from each pair of signals. and Adaptive reachable density temporal clustering to extract signal parameters. and The second frequency, second bandwidth, and second field strength are defined, and their distances are determined to be less than three times the corresponding root mean square error, as expressed in the following: If it meets the criteria, it is classified as one category; otherwise, it is not. S404. Repeat steps S402-S403 until all sensing locations have completed pairwise clustering of signal measurement parameters from at least two separate measurements, thus obtaining the spatial dimension classes. ,in For time dimension category number, This refers to the index of the signal parameters contained in the class. For time dimension class index; S405, Regarding spatial dimension classes The model parameters in the data are merged and represented as follows: S406. Using a positioning algorithm, analyze the fused orientation and its corresponding root mean square error. The electromagnetic target position is obtained by fusion.

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