CN109828952B - PCM system satellite telemetry data classification extraction method and system - Google Patents
PCM system satellite telemetry data classification extraction method and system Download PDFInfo
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Abstract
The invention provides a method and a system for classifying and extracting telemetry data of a PCM system satellite, which comprises the following steps: step 1: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path; step 2: reading original telemetry data of the satellite; and step 3: performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target category telemetry frame according to the category attribute; and 4, step 4: all or a portion of the target class telemetry data in the raw telemetry data of the satellite is acquired. The invention solves the problem that different types of telemetering data can not be classified in the satellite testing process and then are provided for users only needing specific types of telemetering data, realizes the high-efficiency classification of the large-data-volume telemetering data of the PCM system satellite, and meets the requirements of different subsystem users of the satellite on the high-efficiency analysis and use of the telemetering data of the target type.
Description
Technical Field
The invention relates to the field of satellite data processing, in particular to a method and a system for classifying and extracting telemetry data of a PCM system satellite. In particular to a method and a system for efficiently classifying and extracting satellite telemetry data based on a PCM telemetry system.
Background
With the development of satellite development technology, the functions of satellites are rich continuously, the satellite telemetry is refined continuously, the telemetry data is stored in corresponding data storage areas after the whole satellite telemetry acquisition and framing are finished, various telemetering data storage areas are formed, such as delay telemetry, packing telemetry, storage section telemetry, memory unloading telemetry and the like, besides real-time telemetering data which is transmitted instantly is acquired, and each telemetry category is divided into a plurality of subcategories according to different data sources. The transmission path of the telemetering data is continuously developed, the telemetering of the measuring and controlling channel is a traditional telemetering transmission mode, and the data transmission channel also becomes an important path of telemetering data transmission along with the improvement of the telemetering technology. The data volume of the telemetering data downloaded from the data transmission channel is much larger than that of the telemetering data downloaded from the measurement and control channel, one part of the telemetering data is the same as that of the telemetering data transmitted by the measurement and control channel, the telemetering data of the data transmission channel is the special telemetering data transmitted by the data transmission channel, the telemetering data of the data transmission channel is stored in the fixed memory of the satellite system platform when a data frame is generated, and the telemetering data of the data transmission channel is downloaded to the ground system together when the data transmission channel transmits payload.
Currently, in a satellite factory testing process, designers of different institutions or different subsystems need to pay attention to or need specific types of telemetry data of the specialized departments when performing telemetry data analysis. However, the satellite ground test system only realizes unified reception and processing of the telemetry data at present, and there is no efficient means for classifying different types of telemetry data, and even impossible for finely classifying subclasses of the same type of telemetry data, so as to provide required specific types of telemetry data for designers of subsystems or institutions.
In the prior art, satellite system engineering participation subsystems are multiple, functions are rich, satellite telemetering data are large in amount and multiple in types, but different types of telemetering data are classified without an efficient means and provided for users only needing specific types of telemetering data, the independence and the specialty requirements for the telemetering data cannot be met, on one hand, the efficiency of data analysis is low, and on the other hand, a lot of process resources are wasted.
For example, patent document CN107766448A (application No. 201710877196.6) discloses a rule-based satellite telemetry data analysis system, which includes a rule editing system, as an input port of a diagnostic rule, providing two rule editing modes of imaging and script, writing diagnostic rules such as association judgment, condition judgment, mode judgment, mathematics and logic operation for single-dimensional telemetry and multi-dimensional telemetry by associating satellite telemetry parameters, and the rule editing system is provided with a rule base; and the online analysis subsystem reads the rules compiled by the user from the rule base, loads the rules into an analysis and judgment process, receives the telemetering physical quantity data from the network, analyzes and diagnoses the real-time telemetering data according to the rules by the analysis process, writes the judgment result into a result database, and sends the judgment result out through the network.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method and a system for classifying and extracting telemetry data of a PCM system satellite.
The invention provides a PCM system satellite telemetry data classification and extraction method, which comprises the following steps:
step 1: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path;
step 2: reading original telemetry data of the satellite according to the telemetry data input and output file path, and initializing and setting a current processing position at an initial position of the original telemetry data of the satellite;
and step 3: from the current processing position, performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target type telemetry frame according to the telemetry frame characteristic attribute corresponding to the telemetry data to be processed and the type attribute of the target data to be classified and extracted;
and 4, step 4: and acquiring all or part of target class telemetry data in the satellite raw telemetry data according to the locked target class telemetry frame.
Preferably, the telemetry frame characteristic attribute corresponding to the telemetry data to be processed includes four basic parameters, namely a telemetry frame synchronization word, a telemetry frame length ZLen, an offset position of a telemetry frame identification word, and a telemetry frame identification word length;
the target data to be classified and extracted is one or more;
the category attribute of the target data to be classified and extracted comprises a telemetering category identification word and a telemetering category name;
the telemetry data input output file path comprises: the method comprises the steps of classifying and extracting paths of original telemetry data files of the satellite and classifying and extracting storage paths of the telemetry data.
Preferably, the step 2 includes:
and reading in the original telemetry data of the satellite according to the paths of the original telemetry data files of the satellite needing to be classified and extracted, and initializing the current processing position at the initial position of the original telemetry data of the satellite.
Preferably, the step 3 comprises:
step 3.1: matching telemetry frame synchronization words starting from the current processing position P; if the telemetry frame synchronization words are not matched, the method enters step 3.2 to continue execution; if the telemetry frame synchronization words are matched, the step 3.3 is carried out continuously;
step 3.2: judging whether the data length after the current processing position P is larger than or equal to the length of the telemetry frame, if so, updating the current processing position to be the position of the next telemetry word, and returning to the step 3.1 to continue execution; if not, indicating that no effective telemetering frame exists after the current processing position, and ending the process;
step 3.3: starting from the position of the telemetry frame synchronization word successfully matched, locking a target category telemetry frame according to the offset position of the telemetry identification word and the length of the telemetry frame identification word, and judging whether the telemetry word at the offset position is matched with the telemetry category identification word; if the telemetering type identification words are not matched, the step 3.4 is entered for continuous execution; if the telemetering type identification words are matched, the step 3.5 is carried out continuously;
step 3.4: judging that the telemetry frame successfully matched is not the telemetry data which meets the category attribute of the target data needing to be classified and extracted, skipping the data of the telemetry frame successfully matched, namely starting from the position of the telemetry frame synchronization word, updating the position of the telemetry frame after skipping the data with the length ZLen of the telemetry frame to be the current processing position P, and returning to the step 3.1 to continue execution;
step 3.5: locating the telemetry frame successfully matched as the telemetry data meeting the category attribute of the target data needing to be classified and extracted, and entering step 4 to continue execution, wherein the telemetry data meeting the category attribute of the target data needing to be classified and extracted is recorded as: category attribute telemetry data.
Preferably, the step 4 comprises:
step 4.1: storing the category attribute telemetry data;
step 4.2: updating the current processing position to the position after the telemetry data of the category attribute, namely skipping the data of the length ZLen of the telemetry frame; judging whether the data length after the current processing position P is smaller than the telemetry frame length ZLen, if so, indicating that no effective telemetry frame exists after the current position, finishing data search, and ending the process; otherwise, updating the current processing position to the position of the next telemetry word, and returning to the step 3 to continue executing;
the step 4.1 comprises the following steps:
according to the category attribute telemetering data positioned in the step 3, identifying data with the length ZLen of the telemetering frame starting from the position of the telemetering frame synchronous word successfully matched as a frame of complete telemetering data of the target category telemetering frame, and acquiring a frame of complete telemetering data of the target category telemetering frame; judging whether a source code file named by a telemetering type name exists under a storage path according to the classified and extracted target data storage path, if not, creating a file named by the telemetering type name, and writing the acquired complete telemetering data content of one frame of the target type telemetering frame into the file named by the telemetering type name; and if so, directly writing the acquired complete telemetry data content of one frame of the target type telemetry frame into a source code file named by the telemetry type name.
The invention provides a PCM system satellite telemetry data classification and extraction system, which comprises:
an attribute and path acquisition module: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path;
an original data reading module: reading original telemetry data of the satellite according to the telemetry data input and output file path, and initializing and setting a current processing position at an initial position of the original telemetry data of the satellite;
telemetry frame synchronization locking module: from the current processing position, performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target type telemetry frame according to the telemetry frame characteristic attribute corresponding to the telemetry data to be processed and the type attribute of the target data to be classified and extracted;
target telemetry data storage module: and acquiring all or part of target class telemetry data in the satellite raw telemetry data according to the locked target class telemetry frame.
Preferably, the telemetry frame characteristic attribute corresponding to the telemetry data to be processed includes four basic parameters, namely a telemetry frame synchronization word, a telemetry frame length ZLen, an offset position of a telemetry frame identification word, and a telemetry frame identification word length;
the target data to be classified and extracted is one or more;
the category attribute of the target data to be classified and extracted comprises a telemetering category identification word and a telemetering category name;
the telemetry data input output file path comprises: the method comprises the steps of classifying and extracting paths of original telemetry data files of the satellite and classifying and extracting storage paths of the telemetry data.
Preferably, the raw data reading module: and reading in the original telemetry data of the satellite according to the paths of the original telemetry data files of the satellite needing to be classified and extracted, and initializing the current processing position at the initial position of the original telemetry data of the satellite.
Preferably, the telemetry frame synchronization locking module comprises:
a sync word matching module: matching telemetry frame synchronization words starting from the current processing position P; if the telemetry frame synchronization words are not matched, triggering a first processing end judgment module to continue execution; if the telemetry frame synchronous words are matched, the identification word matching module is triggered to continue executing;
a first processing end determination module: judging whether the data length after the current processing position P is larger than or equal to the length of the telemetry frame, if so, updating the current processing position to be the position of the next telemetry word, and triggering the synchronous word matching module to continue execution; if not, indicating that no effective telemetering frame exists after the current processing position, and ending the process;
a tag word matching module: starting from the position of the telemetry frame synchronization word successfully matched, locking a target category telemetry frame according to the offset position of the telemetry identification word and the length of the telemetry frame identification word, and judging whether the telemetry word at the offset position is matched with the telemetry category identification word; if the telemetering type identification words are not matched, the processing position updating module is triggered to continue executing; if the telemetering type identification words are matched, triggering the telemetering frame data positioning module to continue execution;
a processing location update module: judging that the telemetry frame successfully matched is not the telemetry data which meets the category attribute of the target data needing to be classified and extracted, skipping the data of the telemetry frame successfully matched, namely starting from the position of the telemetry frame synchronization word, updating the position of the telemetry frame after skipping the data with the length ZLen of the telemetry frame to be the current processing position P, and triggering the synchronization word matching module to continue to execute;
a telemetry frame data positioning module: locating the telemetry frame successfully matched as the telemetry data meeting the category attribute of the target data needing to be classified and extracted, and triggering a target telemetry data storage module to continue executing, wherein the telemetry data meeting the category attribute of the target data needing to be classified and extracted is recorded as: category attribute telemetry data.
Preferably, the target telemetry data storage module comprises:
a store category telemetry data module: storing the category attribute telemetry data;
a store category telemetry data module: storing the category attribute telemetry data;
a second flow end determination module: updating the current processing position to the position after the telemetry data of the category attribute, namely skipping the data of the length ZLen of the telemetry frame; judging whether the data length after the current processing position P is smaller than the telemetry frame length ZLen, if so, indicating that no effective telemetry frame exists after the current position, finishing data search, and ending the process; otherwise, updating the current processing position to be the position of the next telemetry word, and triggering the telemetry frame synchronization locking module to continue execution;
the storage class telemetry data module comprises:
a telemetry frame data acquisition module: according to the category attribute telemetering data positioned by the telemetering frame synchronization locking module, identifying data with the length of the telemetering frame from the position of the telemetering frame synchronization word which is successfully matched as one frame of complete telemetering data of the target category telemetering frame, and acquiring one frame of complete telemetering data of the target category telemetering frame; judging whether a source code file named by a telemetering type name exists under a storage path according to the classified and extracted target data storage path, if not, creating a file named by the telemetering type name, and writing the acquired complete telemetering data content of one frame of the target type telemetering frame into the file named by the telemetering type name; and if so, directly writing the acquired complete telemetry data content of one frame of the target type telemetry frame into a source code file named by the telemetry type name.
Compared with the prior art, the invention has the following beneficial effects:
the invention effectively solves the problem that different types of telemetering data can not be classified in the satellite test process and then provided for users only needing specific types of telemetering data. The invention can efficiently realize the classified extraction of the satellite telemetry data of large data volume based on the PCM telemetry system through an optimized algorithm. The method can be applied to all telemetry data classification extraction of satellite models based on a PCM telemetry system by combining with automatic and generalized designs, and can position target telemetry data in telemetry raw data and output to external files corresponding to target telemetry classes in a classification manner only by acquiring the overall definition of the characteristic attribute of a satellite telemetry frame and the class attribute of a target telemetry frame. And finally, the requirements of users of different subsystems of the satellite on high-efficiency analysis and use of the telemetry data of the target category are met.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
fig. 1 is a flow chart of the PCM system satellite telemetry data efficient classification and extraction method according to the invention.
Fig. 2 is a schematic flow chart of steps S103 and S104 in the PCM system satellite telemetry data efficient classification and extraction method according to the invention.
Fig. 3 is a schematic flow chart of a preferred embodiment of the PCM system satellite telemetry data efficient classification and extraction method according to the invention.
Fig. 4 is a flowchart illustrating a preferred embodiment of the PCM system satellite telemetry data efficient classification and extraction method according to the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Referring to fig. 1, a method for classifying and extracting telemetry data of a PCM system satellite according to the present invention includes:
step S101: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path; further, the telemetry frame characteristic attribute corresponding to the telemetry data to be processed is a characteristic attribute generally defined by the satellite model to which the telemetry data to be processed belongs.
Step S102: reading original telemetry data of the satellite according to the telemetry data input and output file path, and initializing and setting a current processing position at an initial position of the original telemetry data;
step S103: from the current processing position, performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target type telemetry frame according to the telemetry frame characteristic attribute corresponding to the telemetry data to be processed and the type attribute of the target data to be classified and extracted;
step S104: and acquiring all or part of target class telemetry data in the satellite raw telemetry data according to the locked target class telemetry frame. And further, outputting the acquired target category telemetry data to an external file.
Specifically, the step S101 includes:
the telemetry frame characteristic attributes corresponding to the telemetry data needing to be processed comprise four basic parameters of a telemetry frame synchronization word, a telemetry frame length ZLen, an offset position of a telemetry frame identification word and a telemetry frame identification word length;
the target data to be classified and extracted is one or more;
the category attribute of the target data to be classified and extracted comprises a telemetering category identification word and a telemetering category name;
the telemetry data input output file path comprises: the method comprises the steps of classifying and extracting paths of original telemetry data files of the satellite and classifying and extracting storage paths of the telemetry data.
Specifically, the step S102 includes:
and reading in the original telemetry data of the satellite according to the paths of the original telemetry data files of the satellite needing to be classified and extracted, and initializing the current processing position at the initial position of the original telemetry data of the satellite.
Specifically, the step S103 includes:
step S113: matching telemetry frame synchronization words starting from the current processing position P; if the telemetry frame synchronization words are not matched, the method proceeds to step S123 to continue execution; if the telemetry frame synchronization words match, the step S133 is entered for further execution;
step S123: judging whether the data length after the current processing position P is larger than or equal to the length of the telemetry frame, if so, updating the current processing position to be the position of the next telemetry word, and returning to the step S113 to continue execution; if not, indicating that no effective telemetering frame exists after the current processing position, and ending the process;
step S133: starting from the position of the telemetry frame synchronization word successfully matched, locking a target category telemetry frame according to the offset position of the telemetry identification word and the length of the telemetry frame identification word, and judging whether the telemetry word at the offset position is matched with the telemetry category identification word; if the telemetering type identifier words are not matched, the step S143 is entered for continuous execution; if the telemetry type identifier words are matched, the operation proceeds to step S153;
step S143: judging that the telemetry frame successfully matched is not the telemetry data which meets the category attribute of the target data needing to be classified and extracted, skipping the data of the telemetry frame successfully matched, namely starting from the position of the telemetry frame synchronization word, updating the position of the telemetry frame after skipping the data with the length ZLen of the telemetry frame to be the current processing position P, and returning to the step S113 to continue execution;
step S153: locating the telemetry frame successfully matched as the telemetry data meeting the category attribute of the target data needing to be classified and extracted, and entering step S104 to continue execution, wherein the telemetry data meeting the category attribute of the target data needing to be classified and extracted is recorded as: category attribute telemetry data.
Specifically, the step S104 includes:
step S114: storing the category attribute telemetry data;
step S124: updating the current processing position to the position after the telemetry data of the category attribute, namely skipping the data of the length ZLen of the telemetry frame; judging whether the data length after the current processing position P is smaller than the telemetry frame length ZLen, if so, indicating that no effective telemetry frame exists after the current position, finishing data search, and ending the process; otherwise, updating the current processing position to the position of the next telemetry word, and returning to the step S103 to continue execution;
the step S114 includes:
according to the category attribute telemetering data positioned in the step S103, data with the length ZLen of the telemetering frame starting from the position of the telemetering frame synchronization word successfully matched is determined as one frame of complete telemetering data of the target category telemetering frame, and one frame of complete telemetering data of the target category telemetering frame is obtained; judging whether a source code file named by a telemetering type name exists under a storage path according to the classified and extracted target data storage path, if not, creating a file named by the telemetering type name, and writing the acquired complete telemetering data content of one frame of the target type telemetering frame into the file named by the telemetering type name; and if so, directly writing the acquired complete telemetry data content of one frame of the target type telemetry frame into a source code file named by the telemetry type name.
The classification and extraction system for the telemetry data of the PCM system satellite can be realized by the step flow of the classification and extraction method for the telemetry data of the PCM system satellite. The PCM system satellite telemetry data classification extraction method can be understood as a preferred example of the PCM system satellite telemetry data classification extraction by a person skilled in the art.
The invention provides a PCM system satellite telemetry data classification and extraction system, which comprises:
an attribute and path acquisition module: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path;
an original data reading module: reading original telemetry data of the satellite according to the telemetry data input and output file path, and initializing and setting a current processing position at an initial position of the original telemetry data of the satellite;
telemetry frame synchronization locking module: from the current processing position, performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target type telemetry frame according to the telemetry frame characteristic attribute corresponding to the telemetry data to be processed and the type attribute of the target data to be classified and extracted;
target telemetry data storage module: and acquiring all or part of target class telemetry data in the satellite raw telemetry data according to the locked target class telemetry frame.
Specifically, the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed includes four basic parameters, namely a telemetry frame synchronization word, a telemetry frame length ZLen, an offset position of a telemetry frame identification word and a telemetry frame identification word length;
the target data to be classified and extracted is one or more;
the category attribute of the target data to be classified and extracted comprises a telemetering category identification word and a telemetering category name;
the telemetry data input output file path comprises: the method comprises the steps of classifying and extracting paths of original telemetry data files of the satellite and classifying and extracting storage paths of the telemetry data.
Specifically, the original data reading module reads in original telemetry data of the satellite according to the paths of the original telemetry data files of the satellite needing to be classified and extracted, and initializes a current processing position to be set at an initial position of the original telemetry data of the satellite.
Specifically, the telemetry frame synchronization locking module comprises:
a sync word matching module: matching telemetry frame synchronization words starting from the current processing position P; if the telemetry frame synchronization words are not matched, triggering a first processing end judgment module to continue execution; if the telemetry frame synchronous words are matched, the identification word matching module is triggered to continue executing;
a first processing end determination module: judging whether the data length after the current processing position P is larger than or equal to the length of the telemetry frame, if so, updating the current processing position to be the position of the next telemetry word, and triggering the synchronous word matching module to continue execution; if not, indicating that no effective telemetering frame exists after the current processing position, and ending the process;
a tag word matching module: starting from the position of the telemetry frame synchronization word successfully matched, locking a target category telemetry frame according to the offset position of the telemetry identification word and the length of the telemetry frame identification word, and judging whether the telemetry word at the offset position is matched with the telemetry category identification word; if the telemetering type identification words are not matched, the processing position updating module is triggered to continue executing; if the telemetering type identification words are matched, triggering the telemetering frame data positioning module to continue execution;
a processing location update module: judging that the telemetry frame successfully matched is not the telemetry data which meets the category attribute of the target data needing to be classified and extracted, skipping the data of the telemetry frame successfully matched, namely starting from the position of the telemetry frame synchronization word, updating the position of the telemetry frame after skipping the data with the length ZLen of the telemetry frame to be the current processing position P, and triggering the synchronization word matching module to continue to execute;
a telemetry frame data positioning module: locating the telemetry frame successfully matched as the telemetry data meeting the category attribute of the target data needing to be classified and extracted, and triggering a target telemetry data storage module to continue executing, wherein the telemetry data meeting the category attribute of the target data needing to be classified and extracted is recorded as: category attribute telemetry data.
Specifically, the target telemetry data storage module includes:
a store category telemetry data module: storing the category attribute telemetry data;
a second flow end determination module: updating the current processing position to the position after the telemetry data of the category attribute, namely skipping the data of the length ZLen of the telemetry frame; judging whether the data length after the current processing position P is smaller than the telemetry frame length ZLen, if so, indicating that no effective telemetry frame exists after the current position, finishing data search, and ending the process; otherwise, updating the current processing position to be the position of the next telemetry word, and triggering the telemetry frame synchronization locking module to continue execution;
the storage class telemetry data module comprises:
a telemetry frame data acquisition module: according to the category attribute telemetering data positioned by the telemetering frame synchronization locking module, identifying data with the length of the telemetering frame from the position of the telemetering frame synchronization word which is successfully matched as one frame of complete telemetering data of the target category telemetering frame, and acquiring one frame of complete telemetering data of the target category telemetering frame; judging whether a source code file named by a telemetering type name exists under a storage path according to the classified and extracted target data storage path, if not, creating a file named by the telemetering type name, and writing the acquired complete telemetering data content of one frame of the target type telemetering frame into the file named by the telemetering type name; and if so, directly writing the acquired complete telemetry data content of one frame of the target type telemetry frame into a source code file named by the telemetry type name.
The present invention will be described in more detail below by way of preferred examples.
Example 1:
referring to fig. 3, in step S801, telemetry frame characteristic attributes defined by the satellite model corresponding to telemetry data to be processed are obtained, where the telemetry frame characteristic attributes include four basic parameters, namely, a telemetry frame synchronization word, a telemetry frame length, an offset position of a telemetry frame identification word, and a telemetry frame identification word length.
Step S802, obtaining the category attribute of one or more target telemetering data extracted by the required classification, wherein the category attribute comprises a telemetering category identification word and a telemetering category name.
Step S803, an input/output file path is obtained, which includes an original telemetry data file path that needs to be classified and extracted, and a storage path of the classified target telemetry data.
And step S804, reading in original telemetry data of the satellite, and initializing a telemetry data starting position as a current processing position.
In step S805, a frame of telemetry frames is locked. Firstly, comparing telemetry frame synchronous words at the current processing position of original telemetry data of the satellite, if the telemetry frame synchronous words are not matched and the data length after the current processing position is greater than the length of the telemetry frame, updating the current processing position to be the next telemetry word, and continuously executing the step S805 to search for the synchronous words; if the data length after the current processing position is smaller than the length of the telemetry frame, indicating that no effective telemetry frame exists after the current processing position, and ending the process; if the syncwords match, indicating that it is the start of a frame of telemetry data, step S806 is performed.
Step S806 locks the target class telemetry frame. Starting from the position of the frame synchronous word positioned in the step S805, judging whether the position field is matched with the identifier word of the target telemetering type according to the offset position attribute of the telemetering identifier word, if not, indicating that the frame telemetering is not the target telemetering type, directly skipping the frame data, namely, starting from the position of the synchronous word, skipping the data of the frame length, taking the data as a new initial search position, updating the position as the current processing position, and starting processing from the step S805; if the identifier words match, it indicates that the telemetry frame is the telemetry data of the target category, and then step S807 is performed.
In step S807, the telemetry data of the target category located in step S806 is the frame length data starting from the position of the sync word, that is, one frame of complete telemetry data of the telemetry frame of the target category, and the data content of the frame is acquired.
Step S808, determining whether a source code file named by the name of the target telemetry class exists in the frame of target telemetry data acquired in step S807 according to a storage path set by the user, if not, creating a new file named by the name of the target telemetry class, and if so, directly writing the new file into the file.
Step S809, after the current processing position is updated to the target telemetry frame, the length of the frame length is directly skipped, and it is determined whether the processing of the satellite original telemetry data is completed. That is, if the data length after the current processing position is smaller than the telemetry frame length, it indicates that there is no valid telemetry frame after the current position, the data search is completed, and the process is ended; and if the data length after the current processing position is larger than the telemetry frame length, updating the current processing position to be the next telemetry word, continuously repeating the steps S805 to S809, and circularly searching the next frame of data until all data frames in the data original code file are processed.
Example 2:
referring to fig. 4, in step S901, a telemetry frame characteristic parameter defined by a satellite model is initialized, and four basic parameters of a telemetry frame synchronization word, a telemetry frame length (ZLen), an offset position of a telemetry frame identifier, and a telemetry frame identifier length of the satellite model are obtained.
Step S902, initializing feature identifiers of target telemetry categories, and acquiring category attributes of one or more pieces of target telemetry data extracted by the required classification, including telemetry category identifier words and telemetry category names.
And step S903, initializing satellite original telemetry data input and output paths, wherein the paths comprise satellite telemetry original file paths and storage paths of the target category telemetry data files extracted in a classified mode.
And step S904, reading in original telemetry data of the satellite according to the original telemetry file path of the satellite, and initializing and setting the current processing position (P) at the initial position of the file.
In step S905, a frame of telemetry frames is locked. Comparing the telemetry frame synchronization words from the position P of the original telemetry data of the satellite, if the telemetry frame synchronization words are not matched and the data length after the position P is greater than the telemetry frame length, updating the position P to be the next telemetry word, namely P +1, and continuing to execute the step S905; if the data length after the P position is smaller than the length of the telemetry frame, indicating that no effective telemetry frame exists after the P position, and ending the process; if the syncwords match, indicating that it is the start of a frame of telemetry data, step S906 is performed.
Step S906, the target class telemetry frame is locked. Starting from the step S905 of locking to the position of a frame synchronous word, judging whether the telemetering word at the position is matched with the identifier word of the target telemetering type according to the offset position of the telemetering identifier word and the telemetering frame identifier word length, if the telemetering word at the position is not matched with the identifier word of the target telemetering type, indicating that the frame telemetering is not the target telemetering type, directly skipping the frame telemetering data, namely, starting from the position of the synchronous word, skipping the data of the frame length, taking the data as a new initial search position, updating P + ZLen, and starting from the step five; if the identifier words match, it indicates that the telemetry frame is the telemetry data of the target category, and then step S907 is performed.
In step S907, a frame of target-class telemetry frame data is acquired. The telemetry data of the target category located in step S906 is data of the frame length starting from the position of the sync word, that is, one frame of complete telemetry data of the telemetry frame of the target category, and the content of the frame data is acquired.
In step S909, the position P is updated to be after the target telemetry frame acquired in step S908, that is, P + ZLen, and it is determined whether all the satellite raw telemetry data has been processed. If the data length after the P position is smaller than the telemetry frame length, indicating that no effective telemetry frame exists after the P position, finishing the data search and ending the process; and if the data length after the position P is greater than the telemetry frame length, updating the current processing position to be the next telemetry word, namely P is P +1, continuing to repeat the steps S905 to S909, and searching the next frame of data in a circulating manner until all data frames in the original telemetry data of the satellite are processed.
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (6)
1. A PCM system satellite telemetry data classification extraction method is characterized by comprising the following steps:
step 1: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path;
step 2: reading original telemetry data of the satellite according to the telemetry data input and output file path, and initializing and setting a current processing position at an initial position of the original telemetry data of the satellite;
and step 3: from the current processing position, performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target type telemetry frame according to the telemetry frame characteristic attribute corresponding to the telemetry data to be processed and the type attribute of the target data to be classified and extracted;
and 4, step 4: acquiring all or part of target type telemetry data in the original telemetry data of the satellite according to the locked target type telemetry frame;
the step 2 comprises the following steps:
reading in original telemetry data of the satellite according to file paths of the original telemetry data of the satellite which needs to be classified and extracted, and initializing and setting a current processing position at an initial position of the original telemetry data of the satellite;
the step 3 comprises the following steps:
step 3.1: matching the telemetry frame synchronization word from the current processing position P; if the telemetry frame synchronization words are not matched, the method enters step 3.2 to continue execution; if the telemetry frame synchronization words are matched, the step 3.3 is carried out continuously;
step 3.2: judging whether the data length after the current processing position P is larger than or equal to the length of the telemetry frame, if so, updating the current processing position to be the position of the next telemetry word, and returning to the step 3.1 to continue execution; if not, indicating that no effective telemetering frame exists after the current processing position, and ending the process;
step 3.3: starting from the position of the telemetry frame synchronization word successfully matched, locking a target category telemetry frame according to the offset position of the telemetry identification word and the length of the telemetry frame identification word, and judging whether the telemetry word at the offset position is matched with the telemetry category identification word; if the telemetering type identification words are not matched, the step 3.4 is entered for continuous execution; if the telemetering type identification words are matched, the step 3.5 is carried out continuously;
step 3.4: judging that the telemetry frame successfully matched is not the telemetry data which meets the category attribute of the target data needing to be classified and extracted, skipping the data of the telemetry frame successfully matched, namely starting from the position of the telemetry frame synchronization word, updating the position of the telemetry frame after skipping the data with the length ZLen of the telemetry frame to be the current processing position P, and returning to the step 3.1 to continue execution;
step 3.5: locating the telemetry frame successfully matched as the telemetry data meeting the category attribute of the target data needing to be classified and extracted, and entering step 4 to continue execution, wherein the telemetry data meeting the category attribute of the target data needing to be classified and extracted is recorded as: category attribute telemetry data.
2. The method for classifying and extracting telemetry data of a PCM system satellite according to claim 1, wherein the telemetry frame characteristic attributes corresponding to the telemetry data to be processed include four basic parameters, namely a telemetry frame synchronization word, a telemetry frame length ZLen, an offset position of a telemetry frame identification word and a telemetry frame identification word length;
the target data to be classified and extracted is one or more;
the category attribute of the target data to be classified and extracted comprises a telemetering category identification word and a telemetering category name;
the telemetry data input output file path comprises: the method comprises the steps of classifying and extracting paths of original telemetry data files of the satellite and classifying and extracting storage paths of the telemetry data.
3. The PCM system satellite telemetry data classification extraction method as claimed in claim 1, wherein the step 4 comprises:
step 4.1: storing the category attribute telemetry data;
step 4.2: updating the current processing position to the position after the telemetry data of the category attribute, namely skipping the data of the length ZLen of the telemetry frame; judging whether the data length after the current processing position P is smaller than the telemetry frame length ZLen, if so, indicating that no effective telemetry frame exists after the current position, finishing data search, and ending the process; otherwise, updating the current processing position to the position of the next telemetry word, and returning to the step 3 to continue executing;
the step 4.1 comprises the following steps:
according to the category attribute telemetering data positioned in the step 3, identifying data with the length ZLen of the telemetering frame starting from the position of the telemetering frame synchronous word successfully matched as a frame of complete telemetering data of the target category telemetering frame, and acquiring a frame of complete telemetering data of the target category telemetering frame; judging whether a source code file named by a telemetering type name exists under a storage path according to the classified and extracted target data storage path, if not, creating a file named by the telemetering type name, and writing the acquired complete telemetering data content of one frame of the target type telemetering frame into the file named by the telemetering type name; and if so, directly writing the acquired complete telemetry data content of one frame of the target type telemetry frame into a source code file named by the telemetry type name.
4. A PCM system satellite telemetry data classification and extraction system is characterized by comprising:
an attribute and path acquisition module: acquiring a telemetry frame characteristic attribute corresponding to telemetry data needing to be processed; acquiring the category attribute of target data to be classified and extracted; acquiring a telemetry data input and output file path;
an original data reading module: reading original telemetry data of the satellite according to the telemetry data input and output file path, and initializing and setting a current processing position at an initial position of the original telemetry data of the satellite;
telemetry frame synchronization locking module: from the current processing position, performing telemetry frame synchronization according to the telemetry frame characteristic attribute corresponding to the telemetry data needing to be processed; after the synchronization is successful, locking a target type telemetry frame according to the telemetry frame characteristic attribute corresponding to the telemetry data to be processed and the type attribute of the target data to be classified and extracted;
target telemetry data storage module: acquiring all or part of target type telemetry data in the original telemetry data of the satellite according to the locked target type telemetry frame;
the original data reading module reads in original telemetry data of the satellite according to original telemetry data file paths of the satellite which need to be classified and extracted, and initializes the current processing position to the initial position of the original telemetry data of the satellite;
the telemetry frame synchronization locking module comprises:
a sync word matching module: matching the telemetry frame synchronization word from the current processing position P; if the telemetry frame synchronization words are not matched, triggering a first processing end judgment module to continue execution; if the telemetry frame synchronous words are matched, the identification word matching module is triggered to continue executing;
a first processing end determination module: judging whether the data length after the current processing position P is larger than or equal to the length of the telemetry frame, if so, updating the current processing position to be the position of the next telemetry word, and triggering the synchronous word matching module to continue execution; if not, indicating that no effective telemetering frame exists after the current processing position, and ending the process;
a tag word matching module: starting from the position of the telemetry frame synchronization word successfully matched, locking a target category telemetry frame according to the offset position of the telemetry identification word and the length of the telemetry frame identification word, and judging whether the telemetry word at the offset position is matched with the telemetry category identification word; if the telemetering type identification words are not matched, the processing position updating module is triggered to continue executing; if the telemetering type identification words are matched, triggering the telemetering frame data positioning module to continue execution;
a processing location update module: judging that the telemetry frame successfully matched is not the telemetry data which meets the category attribute of the target data needing to be classified and extracted, skipping the data of the telemetry frame successfully matched, namely starting from the position of the telemetry frame synchronization word, updating the position of the telemetry frame after skipping the data with the length ZLen of the telemetry frame to be the current processing position P, and triggering the synchronization word matching module to continue to execute;
a telemetry frame data positioning module: locating the telemetry frame successfully matched as the telemetry data meeting the category attribute of the target data needing to be classified and extracted, and triggering a target telemetry data storage module to continue executing, wherein the telemetry data meeting the category attribute of the target data needing to be classified and extracted is recorded as: category attribute telemetry data.
5. The PCM system satellite telemetry data classification and extraction system as claimed in claim 4, wherein the telemetry frame characteristic attributes corresponding to the telemetry data to be processed include four basic parameters of telemetry frame synchronization word, telemetry frame length ZLen, offset position of telemetry frame identification word, and telemetry frame identification word length;
the target data to be classified and extracted is one or more;
the category attribute of the target data to be classified and extracted comprises a telemetering category identification word and a telemetering category name;
the telemetry data input output file path comprises: the method comprises the steps of classifying and extracting paths of original telemetry data files of the satellite and classifying and extracting storage paths of the telemetry data.
6. The PCM system satellite telemetry data classification extraction system of claim 4, wherein said target telemetry data storage module comprises:
a store category telemetry data module: storing the category attribute telemetry data;
a second flow end determination module: updating the current processing position to the position after the telemetry data of the category attribute, namely skipping the data of the length ZLen of the telemetry frame; judging whether the data length after the current processing position P is smaller than the telemetry frame length ZLen, if so, indicating that no effective telemetry frame exists after the current position, finishing data search, and ending the process; otherwise, updating the current processing position to be the position of the next telemetry word, and triggering the telemetry frame synchronization locking module to continue execution;
the storage class telemetry data module comprises:
a telemetry frame data acquisition module: according to the category attribute telemetering data positioned by the telemetering frame synchronization locking module, identifying data with the length of the telemetering frame from the position of the telemetering frame synchronization word which is successfully matched as one frame of complete telemetering data of the target category telemetering frame, and acquiring one frame of complete telemetering data of the target category telemetering frame; judging whether a source code file named by a telemetering type name exists under a storage path according to the classified and extracted target data storage path, if not, creating a file named by the telemetering type name, and writing the acquired complete telemetering data content of one frame of the target type telemetering frame into the file named by the telemetering type name; and if so, directly writing the acquired complete telemetry data content of one frame of the target type telemetry frame into a source code file named by the telemetry type name.
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| CN111130693B (en) * | 2019-11-29 | 2022-07-29 | 北京遥测技术研究所 | Method for real-time automatic route selection and automatic framing of telemetering data stream |
| CN111355524B (en) * | 2020-03-10 | 2021-11-23 | 中国西安卫星测控中心 | Multi-source heterogeneous telemetry data comprehensive processing method for Beidou third satellite |
| CN113722340A (en) * | 2021-08-27 | 2021-11-30 | 科大智能电气技术有限公司 | Processing method and system for remote automatic point table updating based on power distribution device |
| CN114205407B (en) * | 2021-12-16 | 2023-11-10 | 北京润科通用技术有限公司 | Method and device for analyzing pulse code modulation telemetry data |
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