JP6503794B2 - Identification device, identification method and program for identification device - Google Patents

Description

  The present invention relates to an identification device, an identification method, and a program of the identification device, and more particularly to an identification device, an identification method, and a program of the identification device for identifying a wireless station used in digital wireless communication.

  A wireless station identification apparatus is known which has a function of identifying an unknown wireless station by receiving radio waves transmitted by the unknown wireless station and analyzing the characteristics of the frequency fluctuation waveform of the received signal. Radio wave propagation characteristics and transient response of parts of the radio station are reflected in the frequency fluctuation waveform of the radio wave transmitted by the radio station to be identified.

  In relation to the present invention, Patent Document 1 and Patent Document 2 describe a radio station identification apparatus having a function of extracting a frequency fluctuation waveform of a received signal at the rising or falling of the received signal. Patent Document 3 describes a wireless station identification apparatus that identifies a wireless station by using a symbol rate deviation of a received signal as a feature.

Patent No. 4543283 gazette JP, 2011-044937, A Patent No. 4367479

  The wireless station identification devices described in Patent Documents 1 and 2 have frequency fluctuation waveforms at the rise or fall of the reception signal, that is, reception at emission or stoppage of radio waves of the radio station that is the transmission source of the reception signal. Extract the frequency fluctuation waveform of the signal. An unknown radio station is identified based on the similarity between the frequency fluctuation waveform of the received signal and the frequency fluctuation waveform (hereinafter referred to as "teacher data") of a known known radio station registered in the database. Ru.

  The frequency fluctuation waveform of the reception signal is extracted from the state in which the state of the radio wave at the time of emission or stop of the radio wave changes transiently. For this reason, unlike the state where radio waves are stably transmitted, the transient state of the radio waves is easily affected by the state of the power supply of the radio station or aging deterioration. As a result, the reproducibility of the characteristics of the radio station based on transient changes in radio waves is not high. Furthermore, a digital modulation scheme radio station (hereinafter referred to as "digital radio station") is a radio station of analog FM (frequency modulation) modulation scheme that has been generally used (hereinafter referred to as "analog radio station"). The frequency bandwidth is narrower than. For this reason, radio waves emitted from digital radio stations have small frequency fluctuations, making it difficult to identify radio stations based on reception frequency fluctuations.

  Further, Patent Document 3 describes a radio station identification apparatus using a symbol rate deviation as a feature. However, in the technology described in Patent Document 3, for example, when the design value of the symbol rate is 1 Mbps (megabits per second), the variation in symbol rate is generally only about ± 10 bps around 1 Mbps. As a result, a receiver with complex and expensive measurement circuitry is needed to measure such small symbol rate variations. Furthermore, assuming that a radio station to be identified is allocated to each 1 bps symbol rate deviation, the number of radio stations that can be registered in the database is at most about 20, so many radio stations are used in the technology described in Patent Document 3. Can not identify

  As described above, the wireless station identification device described in Patent Document 3 has a problem that it is difficult to identify wireless stations with high accuracy. Further, the wireless station identification device described in Patent Document 3 is complicated and expensive, and there is a problem that it is difficult to construct a database of a large number of wireless stations.

  In addition, when the feature unique to the individual is used instead of the feature unique to the model for identifying the unknown wireless station, the feature of the received signal for each model of the wireless station is databased based on the feature It is difficult to do. Therefore, it is also difficult to specify the manufacturer and model of the wireless station from the result of identifying the wireless station by the feature unique to the individual. As a result, the user of a general radio station identification apparatus must combine information such as the voice and frequency spectrum of the received signal to determine the validity of the identification result, and the type of radio station is identified. There is a problem that the burden on the user of the wireless station identification device is large.

(Object of the Invention)
An object of the present invention is to provide a technology for identifying a type and an individual of a radio station with high accuracy, high speed and easily.

  The identification apparatus according to the present invention includes a feature parameter extraction unit for extracting feature parameters indicating features of a synchronization signal included in a digital signal generated from a wireless signal, and a feature data generation unit for combining the feature parameters and outputting as feature data. And a database unit in which the characteristic parameter based on the radio signal received from the known radio station is associated with the model of the known radio station and the characteristic of the individual of the known radio station and registered as reference data in advance. The reference data corresponding to the model of the wireless station to be identified is retrieved from the database unit based on the feature data based on the wireless signal received from the wireless station to be identified, and the reference data is retrieved based on the retrieved reference data Identification process for identifying the type of the radio station to be identified and identifying the individual of the radio station to be identified It comprises a part, a.

  The identification method of the present invention extracts a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal, combines the feature parameters and outputs as feature data, and receives the feature data from a known wireless station The feature parameter based on a wireless signal is associated with the feature and model of the known wireless station and registered as reference data, and the identification is performed based on the feature data based on the wireless signal received from the wireless station to be identified Searching the reference data corresponding to the model of the target wireless station, identifying the type of the wireless station to be identified based on the retrieved reference data, and identifying an individual of the wireless station to be identified; It is characterized by

  The program of the identification device of the present invention is a computer program included in the identification device, a procedure for extracting a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal, combining the feature parameter and outputting it as feature data Procedure for registering the characteristic parameters based on the radio signal received from a known radio station in association with the characteristics of the type and individual of the known radio station as reference data, received from the radio station to be identified A procedure for searching the reference data corresponding to a model of the radio station to be identified from the reference data based on the feature data based on a radio signal; a radio station for the identification target based on the searched reference data A procedure of identifying a model and identifying an individual of the radio station to be identified is performed.

  The identification device, the identification method, and the program of the identification device of the present invention have an effect that the model and the individual of the radio station can be identified with high accuracy, at high speed and easily.

It is a block diagram which shows the structure of the radio station identification device 100 of 1st Embodiment. It is a figure for demonstrating the timing which a radio station transmits a synchronous signal. It is a block diagram which shows an example of a structure of a synchronizing signal. It is a figure which shows the example of the rising time of the non-modulation wave contained in a synchronous signal, and the example of CW length. It is a figure which shows the example of the length of the preamble contained in a synchronizing signal. It is a figure which shows the example of the waveform pattern of the undefined area | region of a synchronous signal. It is a flowchart which shows the example of a radio station identification process. It is a flowchart which shows the example of a production | generation process of teacher data. It is a block diagram which shows the structure of the radio | wireless station identification apparatus 200 of 2nd Embodiment. It is a flowchart which shows the example of the radio station identification process of the radio station identification device 200 of 2nd Embodiment.

First Embodiment
The wireless station identification apparatus described in the first embodiment can identify the wireless station based on the highly reproducible feature by extracting the feature of the wireless station of the transmission source from the synchronization signal having a stable signal waveform. Do. In digital radio stations, synchronization signals are generated using electronic circuits and electronic components designed based on specifications in order to achieve synchronization performance according to the specifications of the wireless system. Therefore, based on the parameters extracted from the waveform of the synchronization signal, the features unique to the radio station model caused by the circuit configuration of the digital radio station and the features unique to the radio station individual due to the individual differences of the electronic components It can be extracted.

  Specifically, the waveforms of an IQ (in-phase / quadrature-phase) signal or an FM (frequency modulation) detection signal generated from a synchronization signal are analyzed, and parameters such as their signal length, rise time, waveform pattern, etc. It is possible to extract features unique to the type and individual of the wireless station by extracting

  A first embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a block diagram showing the configuration of a radio station identification apparatus 100 according to the first embodiment of the present invention. The wireless station identification apparatus 100 includes an antenna 2, a receiver 3, an A / D (analog to digital) converter 4, a parameter extractor 5, a feature data generator 6, an identification processor 7, a database unit 8, a teacher data generator 9 is provided.

  The antenna 2 receives a radio wave transmitted from a radio station to be identified and outputs a received signal. The receiver 3 is a frequency conversion circuit that converts the frequency of the received signal from a radio frequency to an intermediate frequency to generate an intermediate frequency signal. The intermediate frequency is a signal of lower frequency than the radio frequency. The receiver 3 outputs the intermediate frequency signal to the A / D converter 4.

  The A / D conversion unit 4 is an A / D conversion circuit that converts the intermediate frequency signal input from the reception unit 3 into a digital complex envelope signal that is a digital signal. The A / D conversion unit 4 outputs the digital complex envelope signal to the parameter extraction unit 5.

  The parameter extraction unit 5 analyzes the digital complex envelope signal input from the A / D conversion unit 4 and extracts characteristic parameters (hereinafter referred to as “feature parameters”) included in the synchronization signal of the digital complex envelope signal. Is an electronic circuit. The parameter extraction unit 5 outputs the feature parameter to the feature data generation unit 6. The feature parameters will be described later.

  FIG. 2 is a diagram for explaining the timing at which the transmitter transmits a synchronization signal. A transmitter is a radio station that transmits radio waves. The synchronization signal is a signal for the receiver to synchronize with the transmitter. The synchronization signal is fired at the start of radio wave transmission of the transmitter ("ON" in FIG. 2) prior to data such as voice.

  FIG. 3 is a block diagram showing an example of the configuration of the synchronization signal. As shown in FIG. 3, the synchronization signal has a frame structure including continuous wave (CW), preamble, synchronization word, synchronization burst and the like. The synchronization burst includes information of control channel (control CH) and call name. Also, the synchronization burst has an area (undefined area) in which information is not defined. Since the configuration of the synchronization signal is generally known, the detailed description is omitted. Following the synchronization signal, data such as voice is transmitted.

  As the feature parameters, parameters (undefined parameters) not defined in the transmission scheme used in the wireless station can be used. The characteristic parameters extracted from the synchronization signal include the length of the non-modulated wave, the rise time of the non-modulated wave, the length of the preamble signal, the number of repetitions of the synchronization burst, and the waveform pattern of the undefined region in the synchronization burst . The feature parameters are classified into feature parameters specific to the model of the wireless station that is the transmission source of the received signal and feature parameters unique to the individual of the wireless station. The feature data generation unit 6 combines a plurality of feature parameters input from the parameter extraction unit 5 to generate feature data used for identification of a wireless station.

  The identification processing unit 7 notifies the database unit 8 of feature parameters unique to the model among the feature data input from the feature data generation unit 6. The database unit 8 searches the inside of the database based on the feature parameters included in the feature data input from the identification processing unit 7 and searches for teacher data of a model corresponding to the entered feature parameters. The identification processing unit 7 receives the teacher data searched by the database unit 8 as teacher data used for identification of the wireless station.

  The database unit 8 stores the teacher data generated by the teacher data generation unit 9. The teacher data is reference data which is recorded including, for each model, feature parameters unique to the model and feature parameters unique to the individual. The characteristic parameter unique to the wireless station is stored in the database unit 8 as a part (subset) of teacher data unique to the wireless station for each model of the wireless station. That is, the feature parameter unique to the individual is lower-level data of the feature parameter unique to the model.

  The database unit 8 receives model-specific feature parameters extracted from the signal received from the wireless station from the identification processing unit 7, and searches the database unit 8 using this as a key. The database unit 8 searches the teacher data stored in the database for teacher data of a model that hits the key, and notifies the identification processing unit 7 of the teacher data.

  Types of characteristic parameters unique to the model include the length of the non-modulated wave, the length of the preamble signal, and the number of repetitions of the synchronization burst. These are all numerical values obtained from the synchronization signal, and the database unit 8 uses the feature parameters notified from the identification processing unit 7 as a key, and does not perform complex calculations such as correlation processing, and the search function that the database normally comprises Can easily extract teacher data from the database. For example, the database unit 8 searches, for each type of feature parameter input from the identification processing unit 7, teacher data of a model whose difference in value of the feature parameter is equal to or less than a predetermined threshold value. Alternatively, teacher data of a model in which only the difference between some feature parameter values is equal to or less than the threshold may be retrieved. When there is a plurality of teacher data searched within the range of the threshold value, the database unit 8 may notify the identification processing unit 7 of teacher data of all the searched models.

  Generally, the threshold used for comparing the value of the feature parameter notified from the identification processing unit 7 with the value of the teacher data differs depending on the type of feature parameter. Also, there may be a plurality of threshold values for each type of feature parameter. For example, as the threshold value is a relatively large value, teacher data may be retrieved in which the difference from the values of all types of feature parameters notified from the identification processing unit 7 is equal to or less than the threshold value. Alternatively, among the feature parameters notified from the identification processing unit 7, teacher data having a difference with the value of some types of feature parameters may be searched as the relatively small value of the threshold.

  As described above, the identification processing unit 7 is similar to the feature parameter associated with the feature unique to the device type included in the feature data and the feature parameter associated with the feature unique to the device type included in the teacher data Search teacher data based on degree. As a feature specific to the model, there are a maker name and a model name of the radio station, but the invention is not limited thereto.

  When the type of teacher data searched by the database unit 8 is only one type, the identification processing unit 7 sets the type as the identification result of the wireless station. When the type of teacher data notified from the database unit 8 is two or more types, the identification processing unit 7 weights a plurality of feature parameters included in the feature data for each feature parameter type, and the feature data The model corresponding to the nearest teacher data may be used as the identification result of the wireless station. Alternatively, the identification processing unit 7 may use a plurality of models as the identification result of the wireless station.

  As an example of the type of characteristic parameter unique to the individual of the radio station, there are the rise time of the non-modulated wave and the waveform pattern of the undefined region of the synchronization burst. The teacher data includes individual-specific feature parameters associated with the model of the teacher data. After identifying the model of the wireless station based on the search result of the database unit 8, the identification processing unit 7 is unique to the feature parameter unique to the wireless station included in the feature data and the individual on the wireless station included in the training data. An individual of a radio station is identified by comparing it with the feature parameter of and the result is output.

  The identification of the individual of the wireless station can be performed in a procedure similar to the identification of the model of the wireless station in the database unit 8. For example, the identification processing unit 7 is further specific to the individual from the teacher data searched by the database unit 8 for each type of characteristic parameter unique to the individual included in the feature data input from the feature data generation unit 6 A feature parameter whose difference from the value of the feature parameter is less than a predetermined threshold value is searched. Alternatively, feature parameters in which only the difference between feature parameter values unique to some individuals is equal to or less than the threshold may be retrieved. An individual associated in the training data with the retrieved feature parameter is identified as the source radio station of the received signal.

  As described above, the identification processing unit 7 includes the feature parameter associated with the feature unique to the individual included in the searched teacher data, and the feature parameter associated with the feature unique to the individual included in the feature data. The wireless station is identified based on the similarity of. The characteristic unique to an individual is a characteristic that can distinguish different individuals by the same position model. For example, a feature unique to an individual is a serial number assigned to each individual.

  When there are a plurality of individuals corresponding to the feature parameters searched within the threshold range, the identification processing unit 7 may set all the individuals searched as identification results. In general, the threshold used to compare the value of the feature parameter included in the feature data with the feature parameter of the training data differs depending on the type of feature parameter. Also, there may be a plurality of threshold values for each type of feature parameter. For example, even if the feature parameter of an individual whose difference with the value of all types of feature parameters unique to the individual included in the feature data is equal to or less than the threshold is retrieved from the teacher data, with the threshold being a relatively large value. Good. Alternatively, among the feature parameters unique to the individual, the feature parameters of the individual whose difference with the value of some types of feature parameters is equal to or less than the threshold may be searched, with the threshold being a relatively small value. Furthermore, the identification processing unit 7 weights the matching degree between the value of the feature parameter unique to the individual of the wireless station included in the feature data and the value of the feature parameter unique to the individual included in the teacher data, The individual of the radio station may be identified and the result may be output.

  4 to 6 are diagrams for explaining examples of feature parameters. FIGS. 4 to 6 show, as examples of types of feature parameters, the rise time of the non-modulated wave, the length of the non-modulated wave, the length of the preamble included in the synchronization signal, and the waveform pattern of the undefined region of the synchronization signal. Be In FIGS. 4 to 6, the waveform of the synchronization signal is expressed as a waveform of an analog signal. The horizontal axis of the waveforms of FIGS. 4 to 6 is time, and the vertical axis is amplitude.

  FIG. 4 is a diagram showing an example of the rise time of the non-modulated wave included in the synchronization signal and an example of the length (CW length) of the non-modulated wave. In FIG. 4, the non-modulated wave is shown as a waveform of an IQ signal whose phase is different by 90 degrees. The rise time of the unmodulated wave of model A is T1, and the CW length is T3. The rise time of the CW signal of model B is T2, and the CW length is T4. T1 to T4 are obtained from the waveform of the unmodulated wave envelope. Typical values are, but not limited to, T1 and T2 from 1 ms (milliseconds) to 50 ms, and T3 and T4 from 10 to 100 ms.

  FIG. 5 is a diagram showing an example of the length of the preamble included in the synchronization signal. The preamble length of model A is T5, and the preamble length of model B is T6. Typical values for T5 and T6 are, but not limited to, 10 ms to 50 ms.

  FIG. 6 is a diagram showing an example of the waveform pattern of the undefined region of the synchronization signal. By expressing the amplitude of the waveform pattern as “0” or “1” at fixed time intervals, it is possible to express temporal change in amplitude of the waveform pattern by binary data. The conversion from waveform to binary data may be performed by comparing the amplitude of the waveform with a threshold at predetermined time intervals. In FIG. 6, as an example, the waveform of the model A is a data string D1: 001101000010010110101111, and the waveform of the model B is a data string D2: 100010011111011101111011. By binarizing the waveform data, the feature parameters of the waveform pattern can be treated as a data string. Then, when comparing the feature parameters of the waveform pattern between the teacher data and the feature data, the intercode distance of the data string of the feature parameters can be used as the similarity of the waveform.

  The times T1 to T6 and the data strings D1 to D2 thus extracted are extracted from the synchronization signal in the parameter extraction unit 5 as the feature parameters of the unknown wireless station. The types of feature parameters are not limited to the above, and other parameters that can be extracted from the synchronization signal may be used as feature parameters.

  When the radio station of the transmission source of the radio wave received by the radio station identification apparatus 100 is known, the database unit 8 uses the feature data generated by the feature data generation unit 6 as teacher data of the known radio station. Can be stored. The feature data generated by the feature data generation unit 6 is input to the teacher data generation unit 9. The teacher data generation unit 9 may have a function of accumulating the input feature data. When the teacher data generation unit 9 receives an instruction to register teacher data from the outside, the teacher data generation unit 9 associates teacher data by associating the feature parameters included in the feature data with the features unique to the model of the known radio station and the features unique to the individual. Generate The generated teacher data is stored in the database unit 8.

  The feature unique to the model of the known wireless station and the feature unique to the individual may be input to the teacher data generation unit 9 by the user of the wireless station identification apparatus 100. The user of the wireless station identification apparatus 100 may instruct the generation and registration of teacher data. Thus, the wireless station identification apparatus 100 can register the feature parameters of the radio signal being received in the database unit 8 as teacher data.

  The teacher data generation unit 9 generates teacher data using a value obtained by averaging a plurality of stored feature parameters of the same model or a plurality of feature parameters of the same individual for each type of feature parameter. Good. For example, the teacher data generation unit 9 may obtain feature data from the feature data generation unit 6 multiple times, obtain an average value for each type of feature parameter included in the feature data, and use it as teacher data. By using the average value as the feature parameter, the teacher data can more appropriately represent a known wireless station. The teacher data generation unit 9 may register the median, maximum value or minimum value of the stored feature parameters in the database unit 8 as teacher data.

(Description of Operation of First Embodiment)
Next, the operation of the first embodiment of the present invention will be described in detail with reference to the flowchart. FIG. 7 is a flowchart showing an example of a wireless station identification process of the wireless station identification apparatus 100.

  The receiver 3 receives a radio signal from an external radio station and generates an intermediate frequency signal (steps S01 and S02 in FIG. 7). The A / D converter 4 converts the intermediate frequency signal generated by the receiver 3 into a digital complex envelope signal (S03). The parameter extraction unit 5 analyzes the digital complex envelope signal and extracts feature parameters from the synchronization signal included in the digital complex envelope signal (S04). The feature data generation unit 6 generates feature data by combining the feature parameter unique to the model and the feature parameter unique to the individual (S05). The identification processing unit 7 searches the database unit 8 using the type of feature parameter unique to the model included in the feature data as a key (S06), and acquires teacher data corresponding to the key from the database unit 8 (S07) . The identification processing unit 7 compares the feature parameters included in the feature data with the feature parameters included in the teacher data to identify the type of the wireless station, identifies the individual of the wireless station, and outputs the result (S08) . In step S08, the identification processing unit 7 first identifies the model of the wireless station based on the teacher data notified from the database unit 8, and based on the feature parameter unique to the individual included in the teacher data of the identified model. Identify the radio station individual.

  FIG. 8 is a flowchart illustrating an example of teacher data generation processing. The procedure of steps S11 to S15 of FIG. 8 is the same as that of steps S01 to S05 of FIG. The receiver 3 receives a radio signal from an external radio station and generates an intermediate frequency signal (steps S11 and S12 in FIG. 8). The A / D converter 4 converts the intermediate frequency signal generated by the receiver 3 into a digital complex envelope signal (S13). The parameter extraction unit 5 analyzes the digital complex envelope signal and extracts feature parameters from the synchronization signal included in the digital complex envelope signal (S14). The feature data generation unit 6 generates feature data by combining a feature parameter having a property unique to a model and a feature parameter having a property unique to an individual (S15).

  The teacher data generation unit 9 acquires feature data from the feature data generation unit 6 based on the instruction of generation and registration of teacher data (S16). The teacher data generation unit 9 may accumulate the acquired feature data. The teacher data generation unit 9 registers the acquired feature data in the database unit 8 in association with the information on the model of the wireless station or the information on the individual (S17). Information on the model of the radio station or individual information may be included in the instruction of generation and registration of teacher data.

  The above procedure may be executed by a computer (central processing unit (CPU)) included in the wireless station identification apparatus 100 executing a program. The program may be recorded on a fixed, non-temporary recording medium such as a fixed disk drive or a non-volatile semiconductor memory. The CPU is included in any functional block in the wireless station identification device 100, such as the parameter extraction unit 5. The program may be recorded not only in the recording medium included in the wireless station identification apparatus 100 but also in an apparatus connected to the wireless station identification apparatus 100 via a network. In this case, the CPU of the wireless station identification device 100 downloads a program from the device to the wireless station identification device 100 and executes the program.

(Description of the effect)
The first effect of the wireless station identification apparatus 100 according to the first embodiment is that feature extraction of a highly reproducible wireless station is possible, and high accuracy identification is realized even in a digital wireless station having a small feature of the frequency fluctuation waveform. It can be done. The reason is that the radio station identification apparatus 100 extracts features unique to the model and the individual from the parameters of the synchronization signal which is a stable signal section.

  The second effect is to be able to extract the features of each type and individual of the wireless station. The reason is that feature parameters unique to the wireless station model and feature parameters unique to the wireless station are extracted by analyzing the IQ signal and the FM detection signal obtained from the synchronization signal.

  The third effect is that wireless stations can be identified and identified at high speed. The reason is that, first, the training data corresponding to the model is searched using the model-specific feature parameter, and then the individual is identified based on the individual-specific feature parameter included in the searched teacher data It is from.

  The fourth effect is that the user of the wireless station identification apparatus 100 can easily determine whether the identification result is correct. The reason is that since the type name of the wireless station can be determined by the teacher data, the user can easily know the function and performance of the wireless station to be identified and the usage pattern of the wireless station. It is from. The user buys one radio station for each model in advance, extracts characteristic parameters unique to the model, and registers them in the database unit 8 as teacher data. You can also know the names and so on.

  As described above, the wireless station identification apparatus 100 according to the first embodiment has an effect of being able to identify the type and the individual of the wireless station with high accuracy, at high speed, and easily.

Second Embodiment
FIG. 9 is a block diagram showing the configuration of the radio station identification apparatus 200 according to the second embodiment of the present invention. The wireless station identification device 200 includes a parameter extraction unit 5, a feature data generation unit 6, an identification processing unit 7, and a database unit 8. In the second embodiment, the same components as those of the first embodiment are denoted by the same names and reference numerals, and redundant description will be appropriately omitted.

  The functions of the parameter extraction unit 5, the feature data generation unit 6, the identification processing unit 7, and the database unit 8 included in the wireless station identification device 200 are the same as those of the wireless station identification device 100 according to the first embodiment. That is, the digital complex envelope signal is input to the parameter extraction unit 5. The digital complex envelope signal is a signal obtained by converting a received signal received from a wireless station into a digital signal. The parameter extraction unit 5 analyzes the input digital complex envelope signal, and extracts feature parameters of the synchronization signal of the digital complex envelope signal. The parameter extraction unit 5 outputs the feature parameter to the feature data generation unit 6.

  The feature data generation unit 6 combines a plurality of feature parameters input from the parameter extraction unit 5 to generate feature data.

  The identification processing unit 7 notifies the database unit 8 of feature parameters unique to the model among the feature data input from the feature data generation unit 6. The database unit 8 searches the inside of the database based on the feature parameters input from the identification processing unit 7 and extracts teacher data of a model corresponding to the input feature parameters. The identification processing unit 7 receives the teacher data searched by the database unit 8.

  That is, based on the feature data based on the wireless signal received from the wireless station to be identified, the identification processing unit 7 selects the reference data corresponding to the model of the wireless station to be identified from the reference data registered in the database unit 8. Search for. Then, the identification processing unit 7 identifies the type of the radio station to be identified based on the retrieved reference data and identifies the radio station to be identified.

  The database unit 8 stores teacher data. The teacher data includes, for each model, feature parameters unique to the model and feature parameters unique to the individual. The feature parameter unique to the wireless station is stored in the database unit 8 as a part of teacher data unique to the wireless station model.

  The database unit 8 stores teacher data in which known radio station feature parameters are associated with information on the radio station model and the individual. The database unit 8 receives feature parameters unique to the machine type included in the feature data 6 from the identification processing unit 7, and searches for teacher data stored in the database unit 8 using this as a key. The database unit 8 extracts teacher data corresponding to the key from the teacher data as an identification target, and outputs the teacher data to the identification processing unit 7. In the database unit 8, feature parameters based on radio signals received from known wireless stations are associated with known wireless station model types and individual features and registered in advance as reference data.

  FIG. 10 is a flowchart showing an example of the wireless station identification process of the wireless station identification device 200. The procedure of steps S21 to S25 shown in FIG. 10 is the same as steps S04 to S08 of FIG.

  That is, the parameter extraction unit 5 analyzes the input digital complex envelope signal, and extracts feature parameters from the synchronization signal included in the digital complex envelope signal (step S21 in FIG. 10). The feature data generation unit 6 combines feature parameters unique to a model and feature parameters unique to an individual to create feature data (S22). The identification processing unit 7 searches the database unit 8 using the type of feature parameter unique to the model included in the feature data as a key (S23), and acquires teacher data corresponding to the key from the database unit 8 (S24) . The identification processing unit 7 collates the feature data with the teacher data to identify the model of the wireless station, identifies the individual of the wireless station, and outputs the result (S25). In step S25, the identification processing unit 7 first identifies the model of the wireless station based on the teacher data notified from the database unit 8, and based on the feature parameter unique to the individual included in the teacher data of the identified model. The individual of the radio station may be identified.

  The wireless station identification apparatus 200 of the second embodiment having such a configuration exhibits the following first to fourth effects for the same reason as the wireless station identification apparatus 100 of the first embodiment.

  The first effect is that feature extraction of a highly reproducible wireless station is possible, and highly accurate identification can be realized even for a digital wireless station having a small feature of the frequency fluctuation waveform.

  The second effect is to be able to extract the features of each type and individual of the wireless station.

  The third effect is that the wireless station can be identified at high speed.

  The fourth effect is that the user of the wireless station identification apparatus 200 can easily determine whether the identification result is correct.

  That is, the wireless station identification device 200 according to the second embodiment can also easily identify the type and the individual of the wireless station with high accuracy, at high speed.

  Although the present invention has been described with reference to the embodiments, the present invention is not limited to the above embodiments. The configurations and details of the present invention can be modified in various ways that can be understood by those skilled in the art within the scope of the present invention.

  For example, the database unit 8 may be disposed outside the wireless station identification devices 100 and 200. By arranging the database unit 8 outside and connecting the database unit 8 and a plurality of wireless station identification devices via a network, the operation of the database can be unified.

  The present invention is broadly applicable to fields requiring the ability to identify a transmitter. For example, the present invention can be applied to a radio wave monitoring apparatus for monitoring a radio wave emitted from an illegal radio station or the like.

100, 200 radio station identification device 2 antenna 3 reception unit 4 A / D conversion unit 5 parameter extraction unit 6 feature data generation unit 7 identification processing unit 8 database unit 9 teacher data generation unit

Claims (14)

A feature parameter extraction unit for extracting a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal;
A feature data generation unit that combines the feature parameters and outputs the result as feature data;
The feature parameters based on the radio signal received from a known wireless station are associated with features specific to the model of the known wireless station and features unique to the known wireless station and registered in advance as reference data Database department,
The reference data corresponding to the model of the wireless station to be identified is retrieved from the database unit based on the feature data based on the wireless signal received from the wireless station to be identified, and the reference data is retrieved based on the retrieved reference data An identification processing unit that identifies the type of the radio station to be identified and identifies an individual of the radio station to be identified;
Equipped with
The feature parameter associated with the feature specific to the model of the radio station to be identified includes the length of the non-modulated wave included in the synchronization signal, the length of the preamble signal included in the synchronization signal, and the synchronization signal. Including at least one of the number of synchronization bursts included
Identification device. A feature parameter extraction unit for extracting a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal;
A feature data generation unit that combines the feature parameters and outputs the result as feature data;
The feature parameters based on the radio signal received from a known wireless station are associated with features specific to the model of the known wireless station and features unique to the known wireless station and registered in advance as reference data Database department,
The reference data corresponding to the model of the wireless station to be identified is retrieved from the database unit based on the feature data based on the wireless signal received from the wireless station to be identified, and the reference data is retrieved based on the retrieved reference data An identification processing unit that identifies the type of the radio station to be identified and identifies an individual of the radio station to be identified;
Equipped with
The characteristic parameter associated with the characteristic unique to the individual of the radio station to be identified is the rise time of the non-modulated wave included in the synchronization signal and the waveform pattern of the undefined region of the synchronization burst included in the synchronization signal. Including at least one of
Identification device . The feature parameter associated with the feature specific to the model of the radio station to be identified includes the length of the non-modulated wave included in the synchronization signal, the length of the preamble signal included in the synchronization signal, Including at least one of the number of synchronization bursts included
The identification device according to claim 2 . The feature parameter corresponding to the waveform pattern of the undefined region of the synchronization burst is a data string obtained by binarizing the waveform pattern ,
The identification device described in Claim 2 or 3 . A feature parameter extraction unit for extracting a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal;
A feature data generation unit that combines the feature parameters and outputs the result as feature data;
The feature parameters based on the radio signal received from a known wireless station are associated with features specific to the model of the known wireless station and features unique to the known wireless station and registered in advance as reference data Database department,
The reference data corresponding to the model of the wireless station to be identified is retrieved from the database unit based on the feature data based on the wireless signal received from the wireless station to be identified, and the reference data is retrieved based on the retrieved reference data An identification processing unit that identifies the type of the radio station to be identified and identifies an individual of the radio station to be identified;
Equipped with
The identification processing unit
The reference registered in the database unit by using, as an index, the feature parameter associated with a feature unique to a model included in the feature data based on the wireless signal received from the wireless station to be identified Search the reference data corresponding to a specific model from the data,
Identifying the type of the radio station to be identified based on the retrieved reference data;
According to the comparison result of the feature parameter associated with the feature of the individual included in the retrieved reference data and the feature parameter associated with the feature unique to the individual of the wireless station to be identified included in the feature data based identifying individual radio stations of the identification target,
Identification device. A feature parameter extraction unit for extracting a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal;
A feature data generation unit that combines the feature parameters and outputs the result as feature data;
The feature parameters based on the radio signal received from a known wireless station are associated with features specific to the model of the known wireless station and features unique to the known wireless station and registered in advance as reference data Database department,
The reference data corresponding to the model of the wireless station to be identified is retrieved from the database unit based on the feature data based on the wireless signal received from the wireless station to be identified, and the reference data is retrieved based on the retrieved reference data An identification processing unit that identifies the type of the radio station to be identified and identifies an individual of the radio station to be identified;
Equipped with
The identification processing unit is associated with a feature parameter associated with a feature unique to the model included in the feature data, and a feature unique to the model included in the reference data registered in the database unit. It searches the reference data based on the first similarity and characteristic parameter is the similarity,
The first similarity is obtained by weighting each of the feature parameters associated with the plurality of features unique to the model.
Identification device . A feature parameter extraction unit for extracting a feature parameter indicating a feature of a synchronization signal included in a digital signal generated from a wireless signal;
A feature data generation unit that combines the feature parameters and outputs the result as feature data;
The feature parameters based on the radio signal received from a known wireless station are associated with features specific to the model of the known wireless station and features unique to the known wireless station and registered in advance as reference data Database department,
The reference data corresponding to the model of the wireless station to be identified is retrieved from the database unit based on the feature data based on the wireless signal received from the wireless station to be identified, and the reference data is retrieved based on the retrieved reference data An identification processing unit that identifies the type of the radio station to be identified and identifies an individual of the radio station to be identified;
Equipped with
The identification processing unit is associated with a feature parameter associated with a feature unique to an individual included in the retrieved reference data and a feature parameter unique to the individual identification target radio station included in the feature data Identifying an individual of the radio station to be identified on the basis of a second similarity, which is a similarity between the feature parameter and the feature parameter;
The second similarity is obtained by weighting each of feature parameters associated with a plurality of features of the individual,
Identification device . The feature parameter included in the reference data registered in the database unit is a feature parameter generated by averaging a plurality of the feature parameters obtained from a wireless signal received from the known wireless station.
The identification apparatus as described in any one of Claims 1-7. And a reference data generation unit that generates the reference data based on a plurality of the characteristic parameters obtained from the wireless signal received from the known wireless station.
An identification device as claimed in any one of the preceding claims . A receiving unit that receives a radio signal from a radio station, converts the radio signal into an intermediate frequency signal, and outputs the intermediate frequency signal;
An analog-to-digital converter that converts the intermediate frequency signal into a digital signal;
The identification device according to any one of claims 1 to 9, wherein the identification signal is connected to be input to the feature parameter extraction unit.
A radio station identification device comprising: Extracting a feature parameter indicating a feature of the synchronization signal included in the digital signal generated from the wireless signal;
Combining the feature parameters and outputting as feature data;
The feature parameters based on the radio signal received from a known wireless station are registered as reference data in association with features specific to the model of the known wireless station and features unique to the known wireless station.
The reference data corresponding to the model of the wireless station to be identified is retrieved from the registered reference data based on the feature data based on the radio signal received from the wireless station to be identified;
Identifying the type of the radio station to be identified based on the retrieved reference data and identifying an individual of the radio station to be identified;
The feature parameter associated with the feature specific to the model of the radio station to be identified includes the length of the non-modulated wave included in the synchronization signal, the length of the preamble signal included in the synchronization signal, and the synchronization signal. Including at least one of the number of synchronization bursts included
Identification method . Extracting a feature parameter indicating a feature of the synchronization signal included in the digital signal generated from the wireless signal;
Combining the feature parameters and outputting as feature data;
The feature parameters based on the radio signal received from a known wireless station are registered as reference data in association with features specific to the model of the known wireless station and features unique to the known wireless station.
The reference data corresponding to the model of the wireless station to be identified is retrieved from the registered reference data based on the feature data based on the radio signal received from the wireless station to be identified;
Identifying the type of the radio station to be identified based on the retrieved reference data and identifying an individual of the radio station to be identified;
The characteristic parameter associated with the characteristic unique to the individual of the radio station to be identified is the rise time of the non-modulated wave included in the synchronization signal and the waveform pattern of the undefined region of the synchronization burst included in the synchronization signal. Including at least one of
Identification method . Extracting a feature parameter indicating a feature of the synchronization signal included in the digital signal generated from the wireless signal;
Combining the feature parameters and outputting as feature data;
The feature parameters based on the radio signal received from a known wireless station are registered as reference data in association with features specific to the model of the known wireless station and features unique to the known wireless station.
By using, as an index, the feature parameter associated with the model-specific feature included in the feature data based on the radio signal to be identified from the wireless station to be identified, the registered reference data can be identified from the reference data Search for the reference data corresponding to the model of the radio station;
Identifying the type of the radio station to be identified based on the retrieved reference data;
According to the comparison result of the feature parameter associated with the feature of the individual included in the retrieved reference data and the feature parameter associated with the feature unique to the individual of the wireless station to be identified included in the feature data Identifying an individual of the radio station to be identified based on
Identification method. Extracting a feature parameter indicating a feature of the synchronization signal included in the digital signal generated from the wireless signal;
Combining the feature parameters and outputting as feature data;
The feature parameters based on the radio signal received from a known wireless station are registered as reference data in association with features specific to the model of the known wireless station and features unique to the known wireless station.
A feature parameter associated with a feature unique to the model included in the wireless signal received from the wireless station to be identified; and a feature parameter associated with the feature unique to the model included in the registered reference data; Searching the reference data corresponding to the type of the radio station to be identified from the registered reference data, based on the first similarity, which is the similarity of.
Identifying the type of the radio station to be identified based on the retrieved reference data and identifying an individual of the radio station to be identified;
The first similarity is obtained by weighting each of the feature parameters associated with a plurality of features unique to the model.
Identification method .

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