A TACAN pulse signal recognition and adjustment system

Abstract

This invention discloses a TACAN pulse signal recognition and adjustment system, belonging to the field of communication technology. To address the problem that existing technologies still require manual settings to identify the necessary signals when determining the received signal, increasing operational complexity and subsequent maintenance costs, the TACAN pulse signal recognition and adjustment system includes a pulse signal preprocessing module, a pulse signal acquisition module, a judgment module, a pulse signal monitoring module, a detection and adjustment module, and a pulse signal sensing module. Through cluster calculation, based on the changes in the signal data within each group of signals to be identified, it determines the pulse top dataset, pulse bottom dataset, and pulse ramp dataset, thereby obtaining rising edge data or falling edge data. This eliminates the need for manual settings, automatically completing pulse identification, significantly reducing operational complexity and subsequent maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a TACAN pulse signal identification and adjustment system. Background Technology

[0002] TACAN is a short-range polar coordinate radio navigation system capable of determining the azimuth and distance of a ground station relative to an aircraft. TACAN is a widely used navigation equipment, extensively applied in naval formations, providing navigation services for carrier-based aircraft. Therefore, the reception and processing of TACAN signals is an important direction in electronic reconnaissance and is of great significance. Currently, there are relevant patents regarding TACAN pulse signal recognition and adjustment systems. For example, Chinese patent publication number CN106888005A discloses a TACAN pulse signal recognition device, which includes a delay storage circuit, a threshold processing circuit, a rising edge recognition circuit, a falling edge recognition circuit, a pulse confirmation circuit, a peak extraction circuit, a peak time extension circuit, and a special point calibration. By adding a threshold processing circuit, the device removes low-noise signals after setting a reasonable high threshold. By setting relatively lenient rising and falling edge recognition circuits, it further denoises the pulse signal. By adding a pulse confirmation circuit, it confirms whether the pulse has arrived based on characteristics such as pulse width, extracts the maximum value and time of the pulse, and analyzes the pulse width to further extract pulse data from the delay data, thereby achieving the purpose of extracting certain amplitude values.

[0003] Although this patent application solves the technical problem that the pulse signal waveform is severely distorted due to the harsh external electromagnetic environment and interference from multipath signals, making pulse identification very difficult, the following problems still exist in actual use:

[0004] The efficiency of identifying the required signal when determining the received signal still needs to be improved;

[0005] The need for manual settings to identify pulses increases operational complexity and subsequent maintenance costs. Summary of the Invention

[0006] The purpose of this invention is to provide a TACAN pulse signal recognition and adjustment system. By employing a high-precision scanning method within one working cycle, and by using a preset neural network model to determine the attribute information of each target to be identified, the present invention can effectively improve the target recognition accuracy by combining beamforming technology and neural network technology, thereby solving the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A TACAN pulse signal recognition and adjustment system includes a pulse signal preprocessing module for receiving TACAN pulse signals and preprocessing them, extracting feature parameters from the received pulse signals to provide a basis for subsequent signal processing.

[0009] A pulse signal acquisition module is used to acquire at least one group of TACAN pulse signal data to be identified from a set of TACAN pulse signals to be identified, wherein the group of TACAN pulse signal data to be identified consists of multiple TACAN pulse signal data that change in the same direction.

[0010] The judgment module is used to determine whether the signal data to be identified in each group of signal data to be identified is continuously rising or continuously falling;

[0011] The pulse signal monitoring module is used to monitor and identify the target signal in real time. By setting up multiple monitoring units, each monitoring unit monitors one signal data to be identified, and multiple channels and signal categories are determined.

[0012] The detection and adjustment module is used to detect the target signal;

[0013] The pulse signal sensing module is used to convert the detected target signal.

[0014] Furthermore, the pulse signal acquisition module includes:

[0015] The group number extraction module is used to extract the TACAN pulse signal set to be identified and determine the group number of TACAN pulse signal data groups in the current TACAN pulse signal set to be identified;

[0016] The scanning module is used to scan each group of TACAN pulse signal data and obtain the number of TACAN pulse signal data in each group of TACAN pulse signal data.

[0017] The group number determination module is used to determine the number of TACAN pulse signal data groups to be extracted based on the specific circumstances of the number of TACAN pulse signal data groups in the TACAN pulse signal data set to be identified and the amount of TACAN pulse signal data in each TACAN pulse signal data group.

[0018] The number of groups of TACAN pulse signal data to be identified is obtained by the following formula:

[0019]

[0020] in, NThis indicates the number of data groups to be extracted from the TACAN pulse signal data set to be identified, and... N To round up, N The minimum value is 1; C p This indicates the average number of pulse signal data points contained in the TACAN pulse signal data group within the set of TACAN pulse signals to be identified. C max and C min This indicates the maximum and minimum number of pulse signal data contained in a single TACAN pulse signal data group; N z This indicates the total number of TACAN pulse signal data groups contained in the set of TACAN pulse signals to be identified; N 0 indicates the preset threshold for comparison of the number of groups; Δ C This indicates the amount of data compensation.

[0021] Furthermore, the pulse signal acquisition module also includes:

[0022] The judgment module is used to retrieve the group number value corresponding to the number of extracted groups of the TACAN pulse signal data group to be identified, and to determine whether the group number value is 1.

[0023] The data group selection module is used to extract the TACAN pulse signal data group to be identified corresponding to the maximum number of pulse signal data contained in a single TACAN pulse signal data group when the group number value is 1, and send it to the judgment module.

[0024] Furthermore, the determination module includes:

[0025] The rising and falling edge data determination module is used to determine whether the signal data to be identified is rising or falling, and to take the signal data to be identified in the corresponding signal data group as rising edge data or falling edge data in one pulse cycle.

[0026] Furthermore, the pulse signal monitoring module includes:

[0027] The main / auxiliary reference pulse generation module identifies the main and auxiliary reference pulse groups based on the results of the detection and adjustment module, and performs azimuth measurement and beacon station identification.

[0028] The current method for identifying the main reference pulse group is as follows: In X mode, if at least 8 pulses with an interval of 12us and 8 pulses with an interval of 18us appear within 12 time intervals of 30us, it is identified as the main reference pulse group; in Y mode, if at least 8 pulses with an interval of 30us appear within 12 time intervals of 30us, it is identified as the main reference pulse group.

[0029] The current method for identifying the secondary reference pulse group is as follows: In X mode, if at least 8 pulses with an interval of 12us and 8 pulses with an interval of 18us appear within 6 time intervals of 24us, it is identified as a secondary reference pulse group; in Y mode, if at least 8 pulses with an interval of 15us appear within 12 time intervals of 15us, it is identified as a secondary reference pulse group.

[0030] Furthermore, the pulse signal acquisition module includes:

[0031] The high and low level data acquisition module is used to acquire high-level signal data sets and low-level signal data sets from the pulse signal set to be identified, by means of data clustering.

[0032] The module for acquiring the signal data set to be identified is used to acquire the pulse signal data set to be identified from the first selected signal dataset.

[0033] The first selected signal dataset is the remaining signal dataset after removing the high-level signal dataset and the low-level signal dataset.

[0034] Furthermore, the module for acquiring the signal data group to be identified includes:

[0035] The high / low level threshold determination unit is used to determine the high level threshold or low level threshold based on the signal data to be identified in the high level signal dataset or the low level signal dataset.

[0036] The signal access unit is used to receive the target signal from the first selected signal dataset. The target signal is the signal data to be identified between the high-level threshold and the low-level threshold. The target signal is processed according to the sampling time information to form at least one group of signal data to be identified.

[0037] Furthermore, the high / low level data acquisition module also includes:

[0038] A range determination unit is used to determine a first data range of the initial high-level signal dataset and a second data range of the initial low-level signal dataset.

[0039] The scanning module is used to perform high-precision scanning of the coverage area of ​​multiple target signals.

[0040] Furthermore, the pulse signal monitoring module also includes:

[0041] The channel identification module, based on the results of the pulse detection module, judges the interval between adjacent pulses to determine the channel and signal category. According to the arrival time of the signal from the pulse detection module and the effective signal of the pulse, it detects whether the interval between adjacent pulses is 12us, 15us, 18us, 24us, 30us, or 36us. If so, the TACAN signal is within the type that needs to be identified, and the next step of judgment is performed; if not, it returns to the initial stage to continue detection. If the pulse interval is 15us, 18us, 24us, or 36us, the TACAN signal category is directly determined; if the pulse interval is 12us or 30us, the next adjacent pulse is judged, and the signal category is finally obtained.

[0042] Furthermore, it also includes:

[0043] The processing module is used to receive the target echo signal corresponding to the target signal coverage area, and to process the target echo signal, the target unit vector and the preset deflection angle value using a preset neural network model to obtain the attribute information of each target to be identified within the target signal coverage area; wherein, the attribute information includes at least one of the following: category information, center position information, distance information, speed information and heading angle information.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] 1. This invention obtains signal data groups from the set of signals to be identified, performs cluster calculations on the signals, and determines the pulse top dataset, pulse bottom dataset, and pulse ramp dataset based on the changes in the signal data within each signal data group, thereby obtaining rising edge data or falling edge data. Pulse identification is completed automatically without manual settings, greatly reducing operational complexity and subsequent maintenance costs.

[0046] 2. This invention employs a high-precision scanning method within a single working cycle, and further utilizes a pre-defined neural network model to determine the attribute information of each target to be identified. By combining beamforming technology and neural network technology, the accuracy of target recognition can be effectively improved. Attached Figure Description

[0047] Figure 1 This is an overall module diagram of the TACAN pulse signal recognition and adjustment system of the present invention. Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] To address the technical issue that existing technologies still require manual settings for pulse identification when determining the received signal, increasing operational complexity and subsequent maintenance costs, please refer to [the relevant documentation / reference]. Figure 1 This embodiment provides the following technical solution:

[0050] A TACAN pulse signal identification and adjustment system, comprising:

[0051] The pulse signal preprocessing module is used to receive TACAN pulse signals and preprocess them, extracting feature parameters from the received pulse signals to provide a basis for subsequent signal processing.

[0052] Specifically, the pulse signal preprocessing module mainly extracts feature parameters from the pulse signal to provide a basis for subsequent signal processing.

[0053] The pulse signal acquisition module is used to acquire at least one group of TACAN pulse signal data to be identified from the set of TACAN pulse signals to be identified. The group of TACAN pulse signal data to be identified consists of multiple signals to be identified that change in the same direction.

[0054] Specifically, the pulse signal acquisition module includes:

[0055] The group number extraction module is used to extract the TACAN pulse signal set to be identified and determine the group number of TACAN pulse signal data groups in the current TACAN pulse signal set to be identified;

[0056] The scanning module is used to scan each group of TACAN pulse signal data and obtain the number of TACAN pulse signal data in each group of TACAN pulse signal data.

[0057] The group number determination module is used to determine the number of TACAN pulse signal data groups to be extracted based on the specific circumstances of the number of TACAN pulse signal data groups in the TACAN pulse signal data set to be identified and the amount of TACAN pulse signal data in each TACAN pulse signal data group.

[0058] The number of groups of TACAN pulse signal data to be identified is obtained by the following formula:

[0059]

[0060] in, N This indicates the number of data groups to be extracted from the TACAN pulse signal data set to be identified, and... N To round up, N The minimum value is 1; C p This indicates the average number of pulse signal data points contained in the TACAN pulse signal data group within the set of TACAN pulse signals to be identified. C max and C min This indicates the maximum and minimum number of pulse signal data contained in a single TACAN pulse signal data group; N z This indicates the total number of TACAN pulse signal data groups contained in the set of TACAN pulse signals to be identified; N 0 indicates the preset threshold for comparison of the number of groups; Δ C This indicates the amount of data compensation.

[0061] Meanwhile, the pulse signal acquisition module also includes:

[0062] The judgment module is used to retrieve the group number value corresponding to the number of extracted groups of the TACAN pulse signal data group to be identified, and to determine whether the group number value is 1.

[0063] The data group selection module is used to extract the TACAN pulse signal data group to be identified corresponding to the maximum number of pulse signal data contained in a single TACAN pulse signal data group when the group number value is 1, and send it to the judgment module.

[0064] The above method can extract the number of TACAN pulse signal data groups to be identified based on the actual number of data groups and the data content in each TACAN pulse signal data group. This effectively improves the rationality of setting the number of TACAN pulse signal data groups to be identified, reduces the amount of data to be judged in subsequent judgments, and ensures that the amount of data used for subsequent judgments can provide a data foundation for subsequent judgments, thereby improving the accuracy of data judgment.

[0065] The judgment module is used to determine whether the signal data to be identified in each group of signal data to be identified is continuously rising or continuously falling.

[0066] The pulse signal monitoring module is used to monitor the acquired signal in real time and identify and extract the target signal. By setting up multiple monitoring units, each monitoring unit monitors one signal data to be identified, and multiple channels and signal categories are determined.

[0067] The detection and adjustment module is used to detect the target signal;

[0068] The pulse signal sensing module is used to convert the detected target signal.

[0069] Specifically, the pulse signal sensing module is configured with multiple independent sensing tools and coupling devices, which can realize the individual detection and sensing of signals at different locations. Moreover, pulse signals for transmission and sensing are set separately, which effectively reduces the mutual influence of signals between different locations, ensures that the propagation of pulse signals does not interfere with each other, and at the same time, the propagation and sensing of signals do not affect each other, thereby improving the signal recognition accuracy and recognition efficiency of the entire system.

[0070] The judgment module includes:

[0071] The rising and falling edge data determination module is used to determine whether the signal data to be identified is rising or falling, and to take the signal data in the corresponding signal data group as the rising edge data or falling edge data in one pulse cycle.

[0072] The pulse signal monitoring module includes:

[0073] The main / auxiliary reference pulse generation module identifies the main and auxiliary reference pulse groups based on the results of the detection and adjustment module, and performs azimuth measurement and beacon station identification.

[0074] The current method for identifying the main reference pulse group is as follows: In X mode, if at least 8 pulses with an interval of 12us and 8 pulses with an interval of 18us appear within 12 time intervals of 30us, it is identified as the main reference pulse group; in Y mode, if at least 8 pulses with an interval of 30us appear within 12 time intervals of 30us, it is identified as the main reference pulse group.

[0075] The current method for identifying the secondary reference pulse group is as follows: In X mode, if at least 8 pulses with an interval of 12us and 8 pulses with an interval of 18us appear within 6 time intervals of 24us, it is identified as a secondary reference pulse group; in Y mode, if at least 8 pulses with an interval of 15us appear within 12 time intervals of 15us, it is identified as a secondary reference pulse group.

[0076] Specifically, the signal after passing through the pulse detection module also enters the main and auxiliary reference pulse group identification submodule; the main and auxiliary reference pulse group identification is divided into the main and auxiliary reference pulse group in X-channel interrogation mode (X mode) and the main and auxiliary reference pulse group in Y-channel interrogation mode (Y mode).

[0077] The pulse signal acquisition module includes:

[0078] The high and low level data acquisition module is used to acquire high-level signal datasets and low-level signal datasets from the set of pulse signals to be identified, by means of data clustering.

[0079] Specifically, the system obtains signal data groups from the set of signals to be identified, performs clustering calculations on the signals, and determines the pulse top dataset, pulse bottom dataset, and pulse ramp dataset based on the changes in the signal data within each data group. This allows the system to obtain rising edge data or falling edge data automatically. Pulse identification is completed automatically without manual settings, greatly reducing operational complexity and subsequent maintenance costs.

[0080] Using similar computational methods such as data clustering, grouping, and partitioning, pulse-top signal data sets and pulse-bottom signal data sets are defined. Simultaneously, the lower limit of the pulse-top signal data set and the upper limit of the pulse-bottom signal data set are identified. The remaining data outside these sets are arranged according to the acquisition time sequence. Based on the upward or downward continuity of adjacent data, rising edge data and falling edge data are distinguished. Since the acquisition time interval is the same, the rising edge duration and falling edge duration can be calculated based on the number of rising and falling edges acquired. Even if the acquisition intervals are different, the total duration of rising and falling edges can be calculated based on the acquisition time corresponding to the acquisition point.

[0081] The module for acquiring the signal data set to be identified is used to acquire the pulse signal data set to be identified from the first selected signal dataset.

[0082] The first selected signal dataset is the remaining signal dataset after removing the high-level signal dataset and the low-level signal dataset.

[0083] The module for acquiring the signal data set to be identified includes:

[0084] The high / low level threshold determination unit is used to determine the high level threshold or low level threshold based on the signal data to be identified in the high level signal dataset or the low level signal dataset.

[0085] The signal access unit is used to receive the target signal from the first selected signal dataset. The target signal is the signal data to be identified between the high-level threshold and the low-level threshold. The target signal is processed according to the sampling time information to form at least one group of signal data to be identified.

[0086] Specifically, processing the target signal data based on the sampling time information to form at least one group of signal data to be identified includes: sorting the target signal data according to the sampling time information in chronological order; removing the isolated time points of the target signal data to be identified, thus forming at least one group of signal data to be identified.

[0087] The high / low level data acquisition module includes:

[0088] The range determination unit is used to determine the first data range of the initial high-level signal dataset and the second data range of the initial low-level signal dataset.

[0089] Specifically, the range determination unit includes a calculation subunit for calculating the initial average value of the signal data to be identified within the initial high-level signal dataset and the secondary average value of the signal data to be identified within the initial low-level signal dataset; an extreme value confirmation unit for determining the first maximum and minimum values ​​of the signal data to be identified within the initial high-level signal dataset and the second maximum and minimum values ​​of the signal data to be identified within the initial low-level signal dataset; and a data range determination unit for determining the first data range of the initial high-level signal dataset based on the first average value, the first maximum value, and the first minimum value; and determining the second data range of the initial low-level signal dataset based on the second average value, the second maximum value, and the second minimum value.

[0090] The scanning module is used to perform high-precision scanning of the coverage area of ​​multiple target signals.

[0091] Specifically, during the high-precision scanning phase, based on the target signal coverage area, this invention utilizes a pre-defined neural network model to process the target unit vector and the currently acquired target echo signal to determine the attribute information of each target to be identified within the target radar coverage area. The attribute information includes at least one of the following: category information, center position information, range information, and velocity information. The center position information represents the target's deflection angle relative to the pulse signal in the horizontal and vertical directions, and the range information represents the target's straight-line distance relative to the pulse signal.

[0092] The pulse signal monitoring module also includes:

[0093] The channel identification module, based on the results of the pulse detection module, judges the interval between adjacent pulses to determine the channel and signal category. According to the arrival time of the signal from the pulse detection module and the effective signal of the pulse, it detects whether the interval between adjacent pulses is 12us, 15us, 18us, 24us, 30us, or 36us. If so, the TACAN signal is within the type that needs to be identified, and the next step of judgment is performed; if not, it returns to the initial stage to continue detection. If the pulse interval is 15us, 18us, 24us, or 36us, the TACAN signal category is directly determined; if the pulse interval is 12us or 30us, the next adjacent pulse is judged, and the signal category is finally obtained.

[0094] The processing module is used to receive the target echo signal corresponding to the target signal coverage area, and use a preset neural network model to process the target echo signal, the target unit vector and the preset deflection angle value to obtain the attribute information of each target to be identified within the target signal coverage area; wherein, the attribute information includes at least one of the following: category information, center position information, distance information, speed information and heading angle information.

[0095] In summary, the TACAN pulse signal recognition and adjustment system of this invention acquires signal data groups from a set of signals to be identified, performs clustering calculations on the signals, and determines the pulse top dataset, pulse bottom dataset, and pulse ramp dataset based on the changes in the signal data within each data group, thereby obtaining rising edge data or falling edge data. This automatic pulse recognition eliminates the need for manual settings, significantly reducing operational complexity and subsequent maintenance costs. Furthermore, the invention employs high-precision scanning within a single work cycle and utilizes a pre-set neural network model to determine the attribute information of each target to be identified. By combining beamforming technology and neural network technology, the target recognition accuracy is effectively improved.

[0096] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A TACAN pulse signal discrimination conditioning system, characterized by, Comprise; Pulse signal preprocessing module, for receiving TACAN pulse signal and preprocessing, the received pulse signal is extracted for the subsequent signal processing to provide the basis; Pulse signal acquisition module, for obtaining at least one to be identified TACAN pulse signal data group from the to be identified TACAN pulse signal set, the to be identified TACAN pulse signal data group is the multiple to be identified signal data of the same direction change; Judgment module, for judging whether the to be identified signal data in each to be identified signal data group is continuously rising or continuously falling; Pulse signal monitoring module, for real-time monitoring and identifying the target signal extracted from the obtained signal, by setting multiple monitoring units, each monitoring unit monitors a to be identified signal data, determines multiple wave channels and signal categories; Detection adjustment module, for detecting the target signal; Pulse signal sensing module, for converting the detected target signal; Pulse signal acquisition module, comprising: Group number extraction module, for extracting the to be identified TACAN pulse signal set, and determining the group number of TACAN pulse signal data group in the current to be identified TACAN pulse signal set; Scanning module, for scanning each TACAN pulse signal data group, and obtaining the number of TACAN pulse signal data in each TACAN pulse signal data group; Group number determination module, for determining the extraction group number of to be identified TACAN pulse signal data group according to the group number of TACAN pulse signal data group in the to be identified TACAN pulse signal set and the number of TACAN pulse signal data in each TACAN pulse signal data group; Wherein, the extraction group number of to be identified TACAN pulse signal data group is obtained by the following formula: ； ； wherein, N represents the number of extracted groups of the TACAN pulse signal data group to be identified, and N is rounded up, N the minimum value is 1; C p represents the average number of pulse signal data covered in the TACAN pulse signal data group contained in the TACAN pulse signal group to be identified; C max and C min represents the maximum and minimum values of the number of pulse signal data contained in a single TACAN pulse signal data group; N z represents the total number of TACAN pulse signal data groups contained in the TACAN pulse signal group to be identified; N 0 represents a preset group number reference comparison threshold value; Δ C represents a data compensation amount; The pulse signal acquisition module further comprises: Call judgment module, for calling the group number value corresponding to the extraction group number of to be identified TACAN pulse signal data group, and judging whether the group number value is 1; Data group selection module, for when the group number value is 1, extracting the to be identified TACAN pulse signal data group corresponding to the maximum pulse signal data number contained in a single TACAN pulse signal data group and sending to the judgment module.

2. A TACAN pulse signal discrimination conditioning system as in claim 1, wherein: The judgment module comprises: Rising and falling edge data determination module, for according to whether the to be identified signal data is rising or falling, taking the to be identified signal data in the corresponding to be identified signal data group as the rising edge data or the falling edge data in a pulse period.

3. A TACAN pulse signal discrimination conditioning system as in claim 2 wherein: the first and second discriminators are each a single stage discriminator. The pulse signal monitoring module comprises: Main reference / auxiliary reference pulse generation module, for identifying main and auxiliary reference pulse groups according to the result of detection adjustment module, and performing azimuth measurement and beacon station identification; Currently, the main reference pulse group is identified, in X mode, in 12 intervals of 30us time, at least 8 intervals of 12us pulse and 8 intervals of 18us pulse appear, then it is judged as the main reference pulse group; In Y mode, in 12 intervals of 30us time, at least 8 intervals of 30us pulse appear, then it is judged as the main reference pulse group; The current auxiliary reference pulse group is identified. In the X mode, at least 8 pulses with an interval of 12us and 8 pulses with an interval of 18us appear in 24us, and the auxiliary reference pulse group is determined; in the Y mode, at least 8 pulses with an interval of 15us appear in 12us, and the auxiliary reference pulse group is determined.

4. A TACAN pulse signal discrimination conditioning system as in claim 3 wherein: the first and second discriminators are each a Schmitt trigger circuit. The pulse signal acquisition module comprises: The high-low level data set acquisition module is used for obtaining the high-level signal data set and the low-level signal data set from the to-be-identified pulse signal set, and the to-be-identified signal data group acquisition module is used for obtaining the to-be-identified pulse signal data group from the first selected signal data set. The first selected signal data set is the signal data set remaining after removing the high-level signal data set and the low-level signal data set.

5. A TACAN pulse signal discrimination conditioning system as in claim 4 wherein: the first and second discriminators are each a Schmitt trigger circuit. The to-be-identified signal data group acquisition module comprises: The high-low level threshold determination unit is used for determining the high-level threshold or the low-level threshold according to the to-be-identified signal data in the high-level signal data set or the low-level signal data set; The signal access unit is used for receiving a target signal from the first selected signal data set, the target signal being the to-be-identified signal data between the high-level threshold and the low-level threshold, and processing the target signal according to the sampling time information to form at least one to-be-identified signal data group.

6. A TACAN pulse signal discrimination conditioning system as in claim 5 wherein: the first and second discriminators are each a Schmitt trigger circuit. The high-low level data set acquisition module comprises: The range determination unit is used for determining a first data range of the initial high-level signal data set and a second data range of the initial low-level signal data set; The scanning module is used for performing high-precision scanning on the multiple target signal coverage ranges.

7. A TACAN pulse signal discrimination conditioning system as in claim 6, wherein: the first and second discriminators are each a single stage discriminator. The pulse signal monitoring module further comprises: The channel identification module is used for determining the channel and the signal category according to the results of the pulse detection module, and detecting whether the adjacent pulse interval is 12us, 15us, 18us, 24us, 30us or 36us according to the arrival time of the signal of the pulse detection module and the pulse effective signal, if yes, the taccan signal is in the type to be identified, and the next step of identification is continued; if not, it returns to the initial detection; if the pulse interval is 15us, 18us, 24us or 36us, the taccan signal category is directly determined; if the pulse interval is 12us or 30us, the next adjacent pulse is determined, and finally the signal category is obtained.

8. A TACAN pulse signal discrimination conditioning system as in claim 7 wherein: the first and second discriminators are each a Schmitt trigger circuit. Further comprising: The processing module is used for receiving the target echo signal corresponding to the target signal coverage range, and processing the target echo signal by using a preset neural network model to obtain the attribute information of each to-be-identified target in the target signal coverage range; wherein the attribute information comprises at least one of the following: category information, center position information, distance information, speed information and heading angle information.

Images