FPGA-based low-false-alarm-rate TACAN pulse real-time detection method and system

Abstract

The invention discloses a low-false-alarm-rate TACAN pulse real-time detection method and system based on an FPGA (Field Programmable Gate Array), and particularly designs the technical field of pulse signal detection, which comprises the following steps: generating a candidate pulse mark from a baseband pulse signal through an improved delay comparison unit, and outputting the candidate pulse mark; performing energy effectiveness discrimination through average energy discrimination, and obtaining energy confidence according to a preset energy range; performing pulse width identification through pulse width discrimination, and comparing the deviation of the standard pulse width to obtain a pulse width confidence coefficient; and finally, performing weighted judgment on the energy confidence coefficient and the pulse width confidence coefficient to obtain a final detection result. A complete pulse quality evaluation system is constructed through a delay comparison, energy and pulse width triple joint discrimination criterion, comprehensive evaluation of pulse quality is realized, a parallel processing architecture, an assembly line design and a precise synchronization mechanism are adopted on a field programmable gate array, it is ensured that a triple discrimination mechanism can be completed in an extremely short time delay, and the accuracy of pulse quality evaluation is improved. And the unification of high-precision detection and high processing real-time performance is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pulse signal detection, and particularly relates to a low false alarm rate TACAN pulse real-time detection method based on FPGA.

[0002] The present application also relates to a low false alarm rate TACAN pulse real-time detection system based on FPGA. BACKGROUND

[0003] TACAN (Tactical Air Navigation) is a polar coordinate short-range radio navigation system that provides distance and bearing information for aircraft through the exchange of pulse signals between ground beacon stations and airborne equipment. TACAN signals contain a series of Gaussian pulses, which constitute inquiry, response, reference, and padding signal units. Accurate and real-time detection of these pulses from received signals is the basis for reliable ranging and positioning of TACAN systems. In a complex battlefield with dense signal background, the signals received by the TACAN receiver often contain a large amount of noise and various co-frequency interference. Therefore, how to achieve high probability detection of pulses under low signal-to-noise ratio conditions while effectively suppressing false alarms has become a key technical problem in TACAN signal processing.

[0004] Xi'an University of Electronic Science and Technology disclosed a pulse detection method named delay comparison method in its 2018 degree thesis "Research and Implementation of TACAN System Positioning and Ranging Technology". This method divides the digital Gaussian pulse signal into two paths, one of which is subjected to a fixed delay (e.g. 1.75 µs), and the other is subjected to amplitude attenuation (e.g. attenuated to 50%), and the two signals are compared by a comparator to produce a reference point at the moment when the pulse rising edge amplitude is equal to the attenuation level. At the same time, a reference point will also be produced at the pulse falling edge. These two reference points together define a time window for identifying the existence of a pulse. In addition, through this timing reference generation method, the problem of level fluctuation caused by noise in the fixed threshold detection method can be overcome to some extent, and the Gaussian pulse is converted into a rectangular pulse for easy digital processing. This scheme mainly relies on the timing characteristics of the pulse for detection, which can effectively suppress noise interference and improve the accuracy of pulse detection.

[0005] Tongfang Electronics Technology Co., Ltd. and other companies disclosed a TACAN signal detection method based on correlation operations in the 10th issue of "Electronic Products World" in 2022. This mechanism generates preset reference pulse sequences as local templates for different operating modes (such as X mode) according to the TACAN protocol, and encodes the received pulse signals according to the same rules (0 / 1). It determines the validity of the signal by calculating the correlation between the received sequence and the local template and detecting the correlation peak. This method utilizes the overall encoding characteristics of the pulse sequence and has good recognition capability for signals with the correct sequence pattern. However, it is highly dependent on prior information about the signal pattern, requiring prior knowledge of the current signal's operating mode and precise encoding rules. This results in poor adaptability in practical applications; mode switching or non-standard signals can lead to detection failure. Furthermore, the high computational complexity of correlation operations places high demands on processor resources, and implementation on a field-programmable gate array (FPGA) consumes a large number of logic units, which is detrimental to the real-time processing and integration of the system.

[0006] The patent "A DME / TACAN Pulse Width Measurement Method Based on FPGA" (Chinese Patent CN114184847B) discloses a high-precision pulse width measurement mechanism. This mechanism utilizes a high-frequency counter to count pulses throughout their duration and filters valid pulses using a preset pulse tolerance range. This method achieves accurate digital measurement of pulse width and effectively eliminates interference signals caused by pulse width distortion. However, this method typically relies on a fixed amplitude threshold to start and stop the counter, making the measurement results susceptible to fluctuations in signal amplitude. When the pulse amplitude fluctuates due to noise or interference, the fixed threshold method may cause deviations in the pulse width measurement value due to the advance or lag of the trigger point (such as the half-peak point). This could lead to the misjudgment and rejection of normal pulses as pulse width distortion signals, or the missed detection of interference pulses whose amplitudes happen to be near the threshold.

[0007] The current methods suffer from several drawbacks: limited discrimination dimensions, lack of comprehensive evaluation mechanisms, and insufficient anti-interference capabilities and reliability. Existing technologies generally rely solely on a single dimension of pulse characteristics for discrimination. Delay comparison methods primarily utilize timing over-threshold characteristics, failing to identify pulse energy anomalies and pulse width distortions. Related algorithms only focus on the coding consistency of the pulse sequence, remaining insensitive to waveform distortion and energy fluctuations in individual pulses. Fixed-threshold pulse width measurement methods, based solely on pulse width parameters, cannot identify pulses with timing or energy anomalies. This single-dimensional discrimination approach cannot jointly analyze and comprehensively evaluate the key physical characteristics of pulses, such as timing, energy, and pulse width, leading to difficulties in fully and accurately identifying true signals in complex interference environments.

[0008] Poor environmental adaptability and rigid parameters and modes: Existing technologies typically use fixed detection parameters or discrimination criteria, or heavily rely on prior mode information, making them unable to adapt to dynamically changing signal environments. Key parameters (such as delay, attenuation factor, and decision threshold) in delay comparison methods and fixed-threshold pulse width measurement methods are usually preset and fixed, making it difficult to cope with signal strength fluctuations and changes in channel conditions. Fixed-threshold pulse width measurement methods are particularly susceptible to signal amplitude fluctuations, leading to measurement errors. Related algorithms require prior knowledge of the signal's operating mode and precise coding rules, resulting in poor adaptability and insufficient robustness when facing mode switching or non-standard signals.

[0009] Balancing processing efficiency with system optimization goals is challenging: some technologies, while pursuing high performance, introduce high computational and resource overhead. For example, related algorithms have high computational complexity, requiring a large number of multiply-accumulate operations. When implemented on a field-programmable gate array (FPGA), they consume significant logic and multiplier resources, posing a severe challenge to real-time processing, system power consumption, and miniaturized integration.

[0010] In summary, existing technologies lack a complete TACAN pulse detection solution that can integrate multi-dimensional information such as timing, energy, and pulse width, while simultaneously achieving high precision, low false alarm rate, strong adaptability, and high real-time performance. Summary of the Invention

[0011] The purpose of this invention is to provide a method and system for real-time detection of low false alarm rate TACAN pulses based on FPGA. By introducing a triple joint discrimination criterion of delay comparison, energy and pulse width, a complete pulse quality evaluation system is constructed to achieve a comprehensive evaluation of pulse quality.

[0012] The technical solution adopted in this invention is as follows: A real-time detection method for low false alarm rate TACAN pulses based on FPGA, the method comprising: Acquire baseband pulse signal; Delay comparison: The baseband pulse signal is passed through the delay comparison unit to generate candidate pulse flags for output. Average energy discrimination: When the delay comparison output pulse candidate flag is reached, the baseband pulse signal is continuously sampled, and the average energy value of each sampling point is obtained to determine the energy validity. The energy confidence level is obtained according to the preset energy range. Pulse width determination: When the delay comparison outputs the pulse candidate flag, the frequency of the baseband pulse signal is measured by a high-frequency counter. The actual pulse width is obtained based on the count value, and the pulse width confidence is obtained by comparing the deviation with the standard pulse width. The final detection result is obtained by weighting the energy confidence level and pulse width confidence level in a comprehensive judgment.

[0013] Furthermore, the delay comparison unit specifically includes a delay circuit, an attenuation circuit, and a comparator. The baseband pulse signal is divided into two paths, which pass through the delay circuit and the attenuation circuit respectively. The comparison circuit receives the output signals of the delay circuit and the attenuation circuit to make a decision and generate a candidate pulse flag. The delay parameters and attenuation factors in the delay circuit and the attenuation circuit are dynamically adjustable.

[0014] Furthermore, the generation of the candidate pulse flag specifically includes: Rising edge reference generation: The baseband pulse signal is divided into two paths. One path passes through a delay circuit with adjustable delay parameters, and the other path passes through an attenuation circuit with adjustable attenuation factors. The two output signals are input to a comparator, and their intersection point corresponds to the set amplitude point of the original pulse rising edge to generate a rising edge reference signal. Falling edge reference generation: By adjusting the delay parameter, a falling edge reference signal is generated at the corresponding amplitude point of the pulse falling edge; A standard rectangular pulse is generated by two reference signals, and glitch suppression logic is added to obtain candidate pulse flags.

[0015] Furthermore, the average energy discrimination specifically includes: When the rising edge of the candidate pulse flag is detected, the baseband pulse signal is continuously sampled and the energy of each sample point is accumulated; when the falling edge of the candidate pulse flag is detected, the average energy value of each sample point is obtained from the energy accumulation result, as shown in the following formula: (1) In the formula, This is the average energy value. For the first n The amplitude value of each sampling point This represents the total number of sampling points during the pulse duration. Energy validity assessment: The average energy value obtained Compare with a preset energy threshold to set a lower energy threshold. With energy upper limit threshold The judgment condition is as follows: (2).

[0016] Furthermore, the energy confidence acquisition specifically includes: The energy confidence score is calculated using a piecewise linear function, as follows: When the average energy value Within the effective range Internal time, energy confidence Based on average energy value Relative to the midpoint of the range The position is calculated using the following formula: (3) when equal to the midpoint of the range At that time, the highest confidence level of 100% is assigned; when exist As the confidence level increases within the interval, it linearly increases from 0% to 100%. when exist As the confidence level increases within the interval, it decreases linearly from 100% to 0%. when Beyond the valid range At that point, the confidence level is 0%.

[0017] Furthermore, the pulse width determination is as follows: Synchronization and Edge Detection: The input candidate pulse flags are processed by a synchronization chain, and the rising and falling edges of the candidate pulse flags are detected. A glitch filtering mechanism is used, and the true pulse edges are identified through majority decision logic. High-precision pulse width measurement: A high-frequency counter is started when a rising edge of the candidate pulse flag is detected, and stopped when a falling edge of the candidate pulse flag is detected. The actual pulse width value is calculated based on the counter value and the high-frequency counter clock period. (4) In the formula, To measure the pulse width, This is the counter value. This is the clock cycle of the high-frequency counter.

[0018] Furthermore, based on the measured pulse width Compared with standard TACAN pulse width Calculate the degree of deviation and the confidence level of pulse width. A piecewise linear function is used for quantitative evaluation, as shown in the following formula: (5) Pulse width confidence The calculation is based on a preset pulse tolerance range. ,in Minimum allowable pulse width, Maximum permissible pulse width; when Equal to standard pulse width At that time, the highest confidence level of 100% is assigned; when exist As the confidence level increases within the interval, it linearly increases from 0% to 100%. when exist As the confidence level increases within the interval, it decreases linearly from 100% to 0%. when Exceeding the pulse tolerance range At that time, the confidence level was set to 0%.

[0019] Furthermore, the comprehensive judgment specifically includes: When the signal output by the delay comparison is not a candidate pulse flag, the average energy discrimination and pulse width discrimination are not performed. When the delay comparison outputs a pulse candidate flag, the discrimination results of delay comparison, average energy discrimination and pulse width discrimination are received in parallel. The confidence-weighted judgment is performed by weighting the energy confidence and pulse width confidence for energy discrimination and pulse width discrimination, as follows: Set energy discrimination weight coefficient Set the pulse width discrimination weight coefficient The weighted confidence level is as follows: (6) Final decision and impulse rejection: Set the weighted confidence threshold as follows. When weighted confidence level If the pulse is valid, a pulse validity flag is generated; otherwise, an invalid flag is generated.

[0020] The second technical solution adopted in this invention is a low false alarm rate TACAN pulse real-time detection module based on FPGA, which adopts a low false alarm rate TACAN pulse real-time detection method based on FPGA. The detection module includes a delay comparison module, an average energy decision module, a pulse width discrimination module and a comprehensive decision module. The delay comparison module is used to receive the baseband pulse signal, split the baseband pulse signal into two paths, and the two signals pass through the delay circuit and the attenuation circuit respectively. The comparison circuit receives the output signals of the delay circuit and the attenuation circuit to make a decision and generate a candidate pulse flag. The average energy decision module receives and confirms the candidate pulse flag output by the delay comparison module. It is used to measure the frequency of the baseband pulse signal through a high-frequency counter, obtain the actual pulse width based on the count value, and obtain the pulse width confidence level by comparing the deviation with the standard pulse width. The pulse width discrimination module receives and confirms the candidate pulse flag output by the delay comparison module, measures the frequency of the baseband pulse signal through a high-frequency counter, obtains the actual pulse width based on the count value, and obtains the pulse width confidence level by comparing the deviation with the standard pulse width. The integrated decision module receives the decision results from the delay comparison module, the average energy decision module, and the pulse width discrimination module, performs weighted judgment on the energy confidence and pulse width confidence, obtains the final detection result, and outputs it.

[0021] Furthermore, the detection module also includes a synchronization chain module, as detailed below: The synchronization delay module is used to set a configurable delay buffer. The candidate pulse flag and the baseband pulse signal are passed through the configurable delay buffer respectively. The delay amount of the delay buffer is equal to the sum of the maximum processing delay of the delay comparison module, the average energy discrimination module, and the pulse width discrimination module and the processing delay of the comprehensive decision module. The result output of the comprehensive decision module arrives at the output gate circuit synchronously with the delayed candidate pulse flag and the baseband pulse signal. Specifically, when the comprehensive decision output pulse valid flag is high, the current candidate pulse flag and baseband pulse signal are allowed to pass and be sent to the subsequent decoding module; when the comprehensive decision output pulse invalid flag is low, the current invalid pulse flag and digital Gaussian pulse signal are rejected.

[0022] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: Multi-dimensional comprehensive discrimination, strong anti-interference capability, and high reliability: Addressing the core deficiency of existing technologies with a single discrimination dimension, this invention introduces energy and pulse width discrimination in parallel, combining them with preliminary timing discrimination to construct a complete pulse quality assessment system. This system can effectively identify and eliminate interference signals that meet the requirements in only one dimension but exhibit anomalies in other dimensions, such as pulses with abnormal energy or pulse width distortion, thereby significantly improving anti-interference capability and detection reliability at the source. Testing shows that in typical complex electromagnetic environments, its false alarm rate is orders of magnitude better than existing technologies relying on a single discrimination dimension.

[0023] Good environmental adaptability and strong robustness: Addressing the poor adaptability issues caused by rigid parameters and strong mode dependence in existing technologies, this invention employs configurable discrimination parameters, dynamic thresholds, and a confidence-weighted decision mechanism. This allows the system to adapt to different signal-to-noise ratio conditions, signal strength fluctuations, and interference scenarios without relying on specific prior information about signal modes. It exhibits stronger fault tolerance and stability when facing complex situations such as pulse deformation and mode uncertainty.

[0024] High processing efficiency and optimized resource utilization: To address the processing bottlenecks caused by highly complex algorithms, this invention employs efficient parallel processing, pipelined architecture, and precise synchronization design on a field-programmable gate array (FPGA). This enables the triple discrimination mechanism to complete within an extremely short latency, achieving nanosecond-level high-precision pulse width measurement while ensuring the real-time performance of the system. This solution avoids resource-intensive paths such as related algorithms, achieving a highly efficient balance between excellent performance and low resource overhead. Attached Figure Description

[0025] Figure 1This is a flowchart illustrating the low false alarm rate TACAN pulse real-time detection method based on FPGA of the present invention. Figure 2 This is a schematic diagram of the improved delay comparison circuit in the FPGA-based real-time detection method for low false alarm rate TACAN pulses of the present invention. Figure 3 This is a flowchart of the average energy discrimination process in the FPGA-based real-time detection method for low false alarm rate TACAN pulses in this invention. Figure 4 This is a flowchart of the pulse width discrimination process in the FPGA-based real-time detection method for low false alarm rate TACAN pulses in this invention. Figure 5 This is a flowchart illustrating the integrated discrimination process in the FPGA-based real-time detection method for low false alarm rate TACAN pulses of this invention. Detailed Implementation

[0026] The present invention will now be described in detail with reference to the accompanying drawings.

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0028] Example This embodiment provides a low false alarm rate TACAN pulse real-time detection system based on FPGA, including a delay comparison module, an average energy decision module, a pulse width discrimination module, and a comprehensive decision module; The delay comparison module is used to receive the baseband pulse signal, split the baseband pulse signal into two paths, and the two signals pass through the delay circuit and the attenuation circuit respectively. The comparison circuit receives the output signals of the delay circuit and the attenuation circuit to make a decision and generate a candidate pulse flag. The average energy decision module receives and confirms the candidate pulse flag output by the delay comparison module. It is used to measure the frequency of the baseband pulse signal through a high-frequency counter, obtain the actual pulse width based on the count value, and obtain the pulse width confidence level by comparing the deviation with the standard pulse width. The pulse width discrimination module receives and confirms the candidate pulse flag output by the delay comparison module, measures the frequency of the baseband pulse signal through a high-frequency counter, obtains the actual pulse width based on the count value, and obtains the pulse width confidence level by comparing the deviation with the standard pulse width. The integrated decision module receives the decision results from the delay comparison module, the average energy decision module, and the pulse width discrimination module, performs weighted judgment on the energy confidence and pulse width confidence, obtains the final detection result, and outputs it.

[0029] This embodiment proposes a real-time TACAN pulse detection method with low false alarm rate based on FPGA, based on this module. Its core is a triple discrimination mechanism. This mechanism innovatively introduces two detection criteria, energy discrimination and pulse width discrimination, on the basis of the traditional delay comparison method, forming a complete TACAN pulse detection mechanism.

[0030] This embodiment is implemented on an FPGA and adopts a modular design approach. Specifically, it includes a delay comparison module, an average energy discrimination module, a pulse width discrimination module, and a comprehensive decision module. Each module employs a pipelined architecture to ensure the real-time performance of the detection process. Figure 1 As shown, the specific steps are as follows: First level of discrimination: delayed comparison.

[0031] This embodiment optimizes the traditional delay comparison method and serves as a preliminary screening method for pulse detection. Figure 2 As shown, the improved delay comparison method splits the input baseband pulse signal into two paths: one path passes through a parameter-adjustable delay circuit, and the other path passes through an attenuation circuit with a configurable attenuation factor. The two signals are then compared by a comparator to generate candidate pulse flags, thus achieving preliminary identification and localization of the pulse waveform. The specific implementation steps are as follows: This embodiment introduces an adaptive delay setting, which dynamically adjusts the typical value of delay parameter T1 (1.75µs) and the typical value of attenuation factor A1 (50%) according to the signal environment and application requirements, in order to adapt to different signal characteristics.

[0032] Through the dynamic reconfiguration capability of the Field Programmable Gate Array (FPGA), the aforementioned dynamically adjustable parameters can be adjusted in real time according to external commands or channel evaluation results, thereby significantly improving the system's adaptability to different signal environments such as signal-to-noise ratio fluctuations and changes in interference types.

[0033] The digital Gaussian pulse signal, also known as the baseband pulse signal, is the digital baseband signal input to the pulse detection system after intermediate frequency acquisition and digital down-conversion preprocessing. The delay comparison process is as follows: Rising edge reference generation: The digital Gaussian pulse signal is divided into two paths, one of which passes through a configurable delay time T1, and the other passes through a programmable attenuator A1. The two signals are input to a comparator, and their intersection point corresponds to the set amplitude point of the rising edge of the original pulse. The difference between the digital signals is considered to be within the threshold range when they intersect.

[0034] Falling edge reference generation: A similar mechanism to the rising edge reference is used. By adjusting the delay parameter T2 to a typical value of 3.5µs, a reference signal is generated at the corresponding amplitude point of the pulse falling edge.

[0035] Pulse shaping and optimization: The output signals of the comparators in the above two processes are subjected to logical operations to generate standard rectangular pulses, and glitch suppression logic is added to improve timing stability.

[0036] Second discrimination: Average energy discrimination This embodiment innovatively introduces average energy discrimination as a second detection criterion based on the traditional delay comparison method, effectively solving the problem of false detection of abnormal energy pulses. Figure 3 As shown, the specific implementation steps are as follows: Energy accumulation start-up: When the improved delay comparison module outputs the rising edge of the candidate pulse flag, the energy discrimination module starts immediately. During the duration of the candidate pulse flag, the input signal is continuously sampled at the system input master clock frequency, and the amplitude value of each sample point is squared and the result is accumulated into the energy accumulator.

[0037] Average Energy Calculation: Upon detecting the falling edge of the candidate pulse flag, the average energy calculation process is triggered. The total value of the energy accumulator is divided by the number of sampling points to obtain the average energy value. The calculation formula is as follows: (1) In the formula, This is the average energy value. The amplitude value at the nth sampling point. This represents the total number of sampling points within the pulse duration.

[0038] Energy efficiency assessment: The calculated average energy value Compare with a preset energy threshold to set a lower energy threshold. Used to filter out noise signals with insufficient energy, setting an upper energy threshold. The criteria for eliminating interference signals with excessive energy are as follows: (2) Confidence assessment output: Based on the energy validity judgment, the energy confidence level is further calculated. To quantify the quality level of pulse energy, the confidence level is calculated using a piecewise linear function, the mathematical expression of which is: (3) When the average energy value Within the effective range Within the time frame, confidence level according to Relative to the midpoint of the range Position calculation: when equal to the midpoint of the range At that time, the highest confidence level of 100% is assigned; when exist As the confidence level increases within the interval, it linearly increases from 0% to 100%. when exist As the confidence level increases within the interval, it decreases linearly from 100% to 0%. when Beyond the valid range At that point, the confidence level is 0%.

[0039] Third level of discrimination: Pulse width discrimination To further improve detection reliability, this embodiment introduces pulse width discrimination as a third detection criterion, effectively solving the false detection problem of pulse width distortion pulses, such as... Figure 4 As shown, the specific implementation steps are as follows: Synchronization and Edge Detection: The input candidate pulse flags are synchronized to eliminate metastability issues and accurately detect the rising and falling edges of the pulses. A glitch filtering mechanism is used to identify the true pulse edges through majority decision logic and automatically filter out noise glitch with too short a duration. High-precision pulse width measurement: A high-frequency counter is started on the rising edge of the pulse and stopped on the falling edge of the pulse. The actual pulse width value is calculated based on the counter value and the system clock cycle. (4) In the formula, To measure the pulse width, This is the counter value. This is the clock cycle of the high-frequency counter.

[0040] Pulse width confidence calculation: based on the measured pulse width Compared with standard TACAN pulse width The typical deviation is 3.5µs to calculate the pulse width confidence level. A piecewise linear function is used for quantitative evaluation, and the confidence level is calculated based on a preset pulse tolerance range. ,in The minimum permissible pulse width, typically 3µs, This is the maximum permissible pulse width, typically 4µs.

[0041] The mathematical expression for this piecewise linear function is: (5) when Equal to standard pulse width At that time, the highest confidence level of 100% is assigned; when exist As the confidence level increases within the interval, it linearly increases from 0% to 100%. when exist As the confidence level increases within the interval, it decreases linearly from 100% to 0%. when Exceeding the pulse tolerance range At that time, the confidence level was set to 0%.

[0042] Comprehensive judgment logic.

[0043] This embodiment employs a comprehensive decision-making mechanism based on necessary conditions and confidence-weighted judgments to make a final decision on the triple discrimination results, such as... Figure 5 As shown, the specific implementation steps are as follows: Discrimination result acquisition: Discrimination results from the delay comparison module, average energy discrimination module, and pulse width discrimination module are received in parallel. Delay comparison module: Pulse existence flag, existence = 1, non-existence = 0, i.e., candidate pulse flag; Energy discrimination module: Energy confidence level (0-100%); Pulse width discrimination module: Pulse width confidence (0-100%).

[0044] To ensure that the above results refer to the same candidate pulse flag, a precise synchronization mechanism is designed within the module. Although the three discrimination modules are processed in parallel to maximize real-time performance, they have different processing delays. The synchronization mechanism is implemented by inserting a configurable delay buffer (FIFO) into the data path. Specifically, the output of the path with shorter processing delay, such as the delay comparison module, is buffered to wait for the results of the path with longer processing delay, such as the energy and pulse width discrimination module. Finally, precise time alignment is achieved in the comprehensive decision logic.

[0045] Necessary condition judgment: First, check if the pulse existence flag of the delay comparison module is 1. If the flag is 0, it is directly determined as an invalid pulse and no further processing is performed; only when the flag is 1 will the subsequent weighted judgment process be entered.

[0046] Confidence-weighted judgment: Based on satisfying the necessary condition for delay comparison, a weighted judgment is made on the confidence levels of the energy discrimination and pulse width discrimination dimensions. Set energy discrimination weight coefficient Set the pulse width discrimination weight coefficient The weighted confidence level can then be calculated: (6) Final decision and impulse rejection: Set the weighted confidence threshold as follows. When weighted confidence level When the pulse is active, a high level indicates a valid pulse; otherwise, a low level indicates an invalid pulse. This is achieved by adjusting the weighting coefficients. , and weighted threshold It allows for flexible control over the relative importance and rigor of the two dimensions of energy discrimination and pulse width discrimination, thereby precisely adjusting the system's detection sensitivity and anti-interference capability.

[0047] To ensure precise time alignment between the decision result and the corresponding candidate pulse flag and digital Gaussian pulse signal, this embodiment employs a synchronization chain technique. The candidate pulse flag and digital Gaussian pulse signal each pass through a configurable delay line, the delay being equal to the sum of the maximum delays of the first three discrimination modules (delay comparison, energy discrimination, and pulse width discrimination) and the delay of the integrated logic decision module. Finally, the output of the integrated logic decision module and the delayed candidate pulse flag and digital Gaussian pulse signal arrive synchronously at the output gating circuit. The output of this gating circuit is controlled by the pulse decision result: when it is high, the candidate pulse flag and digital Gaussian pulse signal are allowed to pass and be sent to the subsequent decoding module; when the flag is low, the candidate pulse flag and digital Gaussian pulse signal are discarded, meaning the synchronous output is the TACAN pulse output signal that has been confirmed as valid after triple discrimination. This corresponds to the high-confidence pulse flag and digital Gaussian pulse signal. Weighted confidence level. As an important pulse quality assessment indicator, it is output synchronously to provide data support for system performance monitoring and advanced signal processing.

[0048] The hardware synchronization decision mechanism of this invention not only ensures the necessity of the basic condition of pulse existence, but also achieves a fine evaluation of pulse quality through confidence-weighted judgment. While ensuring detection reliability, it provides good engineering practicality. Finally, the module outputs a high-confidence pulse flag and a digital Gaussian pulse signal that has been rigorously screened and time-aligned, laying a solid foundation for subsequent accurate decoding.

[0049] This article uses specific embodiments to illustrate the principles and implementation methods of the present invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A real-time detection method for low false alarm rate TACAN pulses based on FPGA, characterized in that, The method includes: Acquire baseband pulse signal; Delay comparison: The baseband pulse signal is passed through the delay comparison unit to generate candidate pulse flags for output. Average energy discrimination: When the delay comparison output pulse candidate flag is reached, the baseband pulse signal is continuously sampled, and the average energy value of each sampling point is obtained to determine the energy validity. The energy confidence level is obtained according to the preset energy range. Pulse width determination: When the delay comparison outputs the pulse candidate flag, the frequency of the baseband pulse signal is measured by a high-frequency counter. The actual pulse width is obtained based on the count value, and the pulse width confidence is obtained by comparing the deviation with the standard pulse width. The final detection result is obtained by weighting the energy confidence level and pulse width confidence level in a comprehensive judgment.

2. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 1, characterized in that, The delay comparison unit specifically includes a delay circuit, an attenuation circuit, and a comparator. The baseband pulse signal is divided into two paths, which pass through the delay circuit and the attenuation circuit respectively. The comparison circuit receives the output signals of the delay circuit and the attenuation circuit, makes a decision, and generates a candidate pulse flag. The delay parameters and attenuation factors in the delay circuit and the attenuation circuit are dynamically adjustable.

3. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 2, characterized in that, The generation of the candidate pulse flag specifically includes: Rising edge reference generation: The baseband pulse signal is divided into two paths. One path passes through a delay circuit with adjustable delay parameters, and the other path passes through an attenuation circuit with adjustable attenuation factors. The two output signals are input to a comparator, and their intersection point corresponds to the set amplitude point of the original pulse rising edge to generate a rising edge reference signal. Falling edge reference generation: By adjusting the delay parameter, a falling edge reference signal is generated at the corresponding amplitude point of the pulse falling edge; A standard rectangular pulse is generated by two reference signals, and glitch suppression logic is added to obtain candidate pulse flags.

4. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 2, characterized in that, The average energy discrimination specifically includes: When the rising edge of the candidate pulse flag is detected, the baseband pulse signal is continuously sampled and the energy of each sample point is accumulated; when the falling edge of the candidate pulse flag is detected, the average energy value of each sample point is obtained from the energy accumulation result, as shown in the following formula: （1） In the formula, This is the average energy value. For the first n The amplitude value of each sampling point This represents the total number of sampling points during the pulse duration. Energy validity assessment: The average energy value obtained Compare with a preset energy threshold to set a lower energy threshold. With energy upper limit threshold The judgment condition is as follows: （2）。 5. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 4, characterized in that, The energy confidence level acquisition specifically includes: The energy confidence score is calculated using a piecewise linear function, as follows: When the average energy value Within the effective range Internal time, energy confidence Based on average energy value Relative to the midpoint of the range The position is calculated using the following formula: （3） when equal to the midpoint of the range At that time, the highest confidence level of 100% is assigned; when exist As the confidence level increases within the interval, it linearly increases from 0% to 100%. when exist As the confidence level increases within the interval, it decreases linearly from 100% to 0%. when Beyond the valid range At that point, the confidence level is 0%.

6. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 1, characterized in that, The pulse width determination is as follows: Synchronization and Edge Detection: The input candidate pulse flags are processed by a synchronization chain, and the rising and falling edges of the candidate pulse flags are detected. A glitch filtering mechanism is used, and the true pulse edges are identified through majority decision logic. High-precision pulse width measurement: A high-frequency counter is started when a rising edge of the candidate pulse flag is detected, and stopped when a falling edge of the candidate pulse flag is detected. The actual pulse width value is calculated based on the counter value and the high-frequency counter clock period. （4） In the formula, To measure the pulse width, This is the counter value. This is the clock cycle of the high-frequency counter.

7. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 6, characterized in that, Based on the measured pulse width Compared with standard TACAN pulse width Calculate the degree of deviation and the confidence level of pulse width. A piecewise linear function is used for quantitative evaluation, as shown in the following formula: （5） Pulse width confidence The calculation is based on a preset pulse tolerance range. ,in Minimum allowable pulse width, Maximum permissible pulse width; when Equal to standard pulse width At that time, the highest confidence level of 100% is assigned; when exist As the confidence level increases within the interval, it linearly increases from 0% to 100%. when exist As the confidence level increases within the interval, it decreases linearly from 100% to 0%. when Exceeding the pulse tolerance range At that time, the confidence level was set to 0%.

8. The FPGA-based real-time detection method for low false alarm rate TACAN pulses according to claim 1, characterized in that, The comprehensive judgment specifically includes: When the signal output by the delay comparison is not a candidate pulse flag, the average energy discrimination and pulse width discrimination are not performed. When the delay comparison outputs a pulse candidate flag, the discrimination results of delay comparison, average energy discrimination and pulse width discrimination are received in parallel. The confidence-weighted judgment is performed by weighting the energy confidence and pulse width confidence for energy discrimination and pulse width discrimination, as follows: Set energy discrimination weight coefficient Set pulse width discrimination weight coefficient The weighted confidence level is as follows: （6） Final Decision and Pulse Removal: Set the weighted confidence threshold as follows: When weighted confidence level If the pulse is valid, a pulse validity flag is generated; otherwise, an invalid flag is generated.

9. A real-time detection system for low false alarm rate TACAN pulses based on FPGA, employing the real-time detection method for low false alarm rate TACAN pulses based on FPGA as described in any one of claims 1 to 8, characterized in that, The inspection system includes a delay comparison module, an average energy decision module, a pulse width discrimination module, and a comprehensive decision module. The delay comparison module is used to receive the baseband pulse signal, split the baseband pulse signal into two paths, and the two signals pass through the delay circuit and the attenuation circuit respectively. The comparison circuit receives the output signals of the delay circuit and the attenuation circuit to make a decision and generate a candidate pulse flag. The average energy decision module receives and confirms the candidate pulse flag output by the delay comparison module. It is used to measure the frequency of the baseband pulse signal through a high-frequency counter, obtain the actual pulse width based on the count value, and obtain the pulse width confidence level by comparing the deviation with the standard pulse width. The pulse width discrimination module receives and confirms the candidate pulse flag output by the delay comparison module, measures the frequency of the baseband pulse signal through a high-frequency counter, obtains the actual pulse width based on the count value, and obtains the pulse width confidence level by comparing the deviation with the standard pulse width. The integrated decision module receives the decision results from the delay comparison module, the average energy decision module, and the pulse width discrimination module, performs weighted judgment on the energy confidence and pulse width confidence, obtains the final detection result, and outputs it.

10. The FPGA-based low false alarm rate TACAN pulse real-time detection system according to claim 9, characterized in that, The detection system also includes a synchronization delay module, as detailed below: The synchronization delay module is used to set a configurable delay buffer. The candidate pulse flag and the baseband pulse signal are passed through the configurable delay buffer respectively. The delay amount of the delay buffer is equal to the sum of the maximum processing delay of the delay comparison module, the average energy discrimination module, and the pulse width discrimination module and the processing delay of the comprehensive decision module. The result output of the integrated decision module arrives at the output gating circuit synchronously with the delayed candidate pulse flag and the baseband pulse signal. Specifically, when the comprehensive decision output pulse valid flag is high, the current candidate pulse flag and baseband pulse signal are allowed to pass and be sent to the subsequent decoding module; When the comprehensive decision output pulse invalid flag is low, the current invalid pulse flag and digital Gaussian pulse signal are removed.

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