Frequency hopping signal stable hopping time estimation method based on adaptive period tracking window

Abstract

The application discloses a frequency hopping signal stable hopping moment estimation method based on an adaptive cycle tracking window and belongs to the field of signal processing. The frequency hopping signal is subjected to spectrum analysis and signal detection, and continuous multiple frames of signal detection marks, signal peak frequency indexes and signal frequency boundary indexes are obtained. Frame-by-frame analysis is conducted on signal frequency index variation, sensitivity environment and frequency hopping moment spectrum overlap effect are considered, and coarse estimation is conducted on the signal frequency hopping moment. The difference value of the real-time frequency hopping moment coarse estimation value is subjected to quasi-real-time effective determination, accumulation average and stable grading statistics, adaptive stable frequency hopping cycle estimation is realized, a stable reference hopping moment is obtained through initial cycle tracking, a stable cycle tracking window is generated, the frequency hopping moment coarse estimation value is tracked and filtered in real time based on the stable cycle tracking window, a double stable tracking state feedback mechanism is set to adaptively realize restart tracking, and a stable frequency hopping moment estimation value is obtained.

Description

Technical Field

[0001] This invention belongs to the field of signal processing, and in particular, it is a method for estimating the stable transition time of frequency hopping signals based on an adaptive periodic tracking window. Background Technology

[0002] Frequency-hopping communication signals are typical non-stationary signals, with their frequencies randomly changing periodically over time. They are characterized by low interception probability and high spectral efficiency, making the reception and processing of frequency-hopping communication signals a crucial research area in signal processing. The first step in receiving and processing non-cooperative frequency-hopping signals is signal detection. During signal detection, the false alarm rate and the missed detection rate are contradictory. To minimize missed detections while maintaining sensitivity, a certain probability of false alarms will occur during detection. Under these conditions, the estimation of the frequency jump timing of the frequency-hopping signal can be inaccurate. Based on the estimated frequency jump timing, the frequency-hopping signal is collected, stored, and measured. However, due to the influence of false alarms, the stored data may exhibit jump-over phenomena, leading to poor accuracy in the measurement of frequency-hopping signal parameters.

[0003] To improve the effectiveness of frequency hopping signal detection and the accuracy of parameter measurement, while also considering the versatility of application scenarios, it is of great significance to study a method for estimating the stable transition time of frequency hopping signals based on an adaptive periodic tracking window. Summary of the Invention

[0004] The purpose of this invention is to estimate the frequency transition time of frequency-hopping signals. Since the false alarm rate and false negative rate are contradictory during signal detection, to meet the requirement of minimizing false negatives under sensitive conditions, a certain probability of false alarms will occur during detection, affecting the accuracy of frequency transition time estimation and subsequent frequency-hopping parameter measurements. This invention proposes a stable frequency-hopping signal transition time estimation method based on an adaptive periodic tracking window. By adaptively and stably estimating the transition period of the frequency-hopping signal, the method performs stable tracking and false alarm filtering on the original coarse estimate of the frequency transition time based on the stable transition period estimation result, improving the stability of the frequency transition time estimation and thus improving the accuracy of subsequent frequency-hopping signal parameter measurements.

[0005] The technical solution for implementing this invention is: a method for estimating the stable transition time of frequency hopping signals based on an adaptive periodic tracking window. The steps are as follows:

[0006] Step 1: Perform spectrum analysis and signal detection on the frequency hopping signal to obtain detection results for multiple consecutive frames, including signal detection markers, signal peak frequency index, signal frequency left boundary index, and signal frequency right boundary index.

[0007] Step 2: Set a configurable frequency index protection interval, design a latching mechanism for the frequency index of the previous valid signal, analyze the signal detection result set obtained in Step 1 frame by frame, and estimate the frequency jump time of the frequency hopping signal by analyzing the changes in the signal frequency index, considering the sensitivity environment and the spectral overlap effect at the frequency jump time, and obtain a rough estimate sequence of frequency jump time values.

[0008] Step 3: Analyze the difference between the coarse estimates of the frequency jump time in Step 2 to obtain the real-time frequency jump period estimation result. Set the effective jump period level, perform quasi-real-time effective judgment, cumulative average and stable level statistics on the real-time results, and obtain the stable frequency jump period estimation result to achieve adaptive stable estimation of the frequency jump period.

[0009] Step 4: Perform initial tracking based on the stable frequency jump period estimation results obtained in Step 3 to obtain the stable reference jump time that satisfies the stable frequency jump period, and generate a stable period tracking window based on this time and the stable jump period estimation results.

[0010] Step 5: Based on the stable periodic tracking window generated in Step 4, the coarse estimate sequence of frequency jump moments in Step 2 is tracked and filtered in real time to obtain a stable frequency jump moment estimate sequence. At the same time, a dual stable tracking state feedback mechanism is set up to adaptively restart tracking.

[0011] Compared with the prior art, the significant advantages of this invention are:

[0012] 1) Quasi-real-time estimation and tiered statistical analysis of the frequency hopping period are performed to achieve adaptive and stable estimation of the frequency hopping period; 2) Stable tracking is performed based on the stable frequency hopping period estimation results, which can filter out false frequency hopping time estimates caused by false alarms; 3) This method has the advantages of simplicity, stability and efficiency. Compared with the traditional signal processing flow, it can adapt to the changes in the frequency hopping period of the frequency hopping signal and stably track the frequency hopping time to obtain a stable frequency hopping time, thereby guiding subsequent data storage and parameter measurement, ensuring that the data for parameter measurement is within one hop, and improving the accuracy of frequency hopping signal parameter measurement. Attached Figure Description

[0013] Figure 1 The flowchart shows a method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window. Detailed Implementation

[0014] 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 a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0015] The technical solutions of the various embodiments of the present invention can be combined with each other, but only if they can be implemented by those skilled in the art. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0016] The following section will further introduce the specific implementation method, as well as the technical difficulties and inventive points of this invention, using this design example as an example.

[0017] Combination Figure 1 The present invention provides a method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window, comprising the following steps:

[0018] Step 1: Perform spectrum analysis and signal detection on the frequency hopping signal to obtain detection results for multiple consecutive frames, including signal detection markers, signal peak frequency index, signal frequency left boundary index, and signal frequency right boundary index, as detailed below:

[0019] Step 11: Perform digital down-conversion processing on the input frequency-hopping signal. The input frequency-hopping signal is located in the intermediate frequency band. The signal spectrum is shifted to the baseband using quadrature demodulation technology to obtain the baseband equivalent complex signal sequence. ,in, and These are the in-phase and quadrature component sequences of the signal, respectively. The imaginary unit, This is a discrete-time index.

[0020] Step 12: Process the equivalent complex signal sequence obtained in Step 11. Perform FFT operation, the number of FFT points is By calculating the spectral amplitude of the complex signal, the energy distribution characteristics of the signal in the frequency domain are analyzed, and the signal detection threshold is determined.

[0021] Step 13: Compare the signal spectral energy with the detection threshold frame by frame, where each... Point operations are performed to obtain a single frame of data, and then the signal detection results for multiple consecutive frames are obtained. ,in, For the total number of frames, the first... Frame detection results It contains the following elements:

[0022] ,

[0023] in, Indicates the first Frame signal detection flag: 1 indicates a signal was detected, 0 indicates no signal was detected. Indicates the first Frame signal peak frequency index Indicates the first Frame signal frequency left boundary index, Indicates the first Frame signal frequency right boundary index, frame index Corresponding time ,in, The time for each frame.

[0024] Step 2: Set a configurable frequency index protection interval, design a latching mechanism for the frequency index of the previous valid signal, analyze the signal detection result set obtained in Step 1 frame by frame, and estimate the frequency jump time of the frequency hopping signal by analyzing the changes in the signal frequency index, considering the sensitivity environment and the spectral overlap effect at the frequency jump time, and obtain a rough estimate sequence of frequency jump time values.

[0025] Step 21: Based on the detection bandwidth With actual sampling bandwidth and FFT points Calculate the number of frequency indices outside the detection bandwidth. :

[0026] ,

[0027] in, For floor operations, the effective frequency index range is then determined. for:

[0028] .

[0029] Step 22: Analyze the detection results frame by frame. , judge the first Frame signal peak frequency index Is it within the effective frequency index range? Inside, obtained the first Frame detection frequency valid marker :

[0030] .

[0031] Step 23: Analyze the detection results frame by frame. Effective markers for detection frequency When the signal detection frequency is valid, the left and right boundary indices of the signal frequency for that frame are latched and updated to obtain the latching result of the left boundary index of the signal frequency. Latch result with right boundary index of signal frequency , specifically:

[0032] ,

[0033] .

[0034] Step 24: Set the frequency protection interval Frame-by-frame analysis of detection results When the first A frequency transition is determined when the frame signal frequency boundary index meets the following conditions: the left boundary of the signal frequency minus the frequency guard interval is greater than the latched result of the right boundary index of the signal frequency, and the right boundary of the signal frequency plus the frequency guard interval is greater than the latched result of the left boundary index of the signal frequency, thus obtaining the first... Frame frequency jump marker , specifically:

[0035] ;

[0036] The innovation of this invention lies in the design of a configurable frequency protection interval, which allows for flexible adjustment of the sensitivity of frequency jump detection.

[0037] Step 25: Analyze the detection results frame by frame. Detection frequency valid marker Frequency jump marker Update the frequency transition state of each frame of signal. The state transition rule is: if the first state transition rule is: No signal was detected in the first frame, so the state is 1; if the first frame... If a signal is detected in the frame, but the signal frequency is outside the valid detection range, the state is 0; if the first frame... The frame detects a signal, the signal frequency is within the valid detection range, and the frequency changes; the state is 2. If the first frame detects a signal, the signal frequency is within the valid detection range, and the frequency changes, the state is 2. A frame detects a signal, the signal frequency is within the valid detection range, and the frequency has not changed. The state is 3, i.e.:

[0038] .

[0039] Step 26: Analyze the frequency transition state frame by frame. The innovation of this invention lies in determining the coarse estimation time of the frequency jump by considering both the sensitivity environmental adaptability and the spectral overlap effect at the frequency jump moment. Specifically, considering the influence of the sensitivity environment, it is possible that an effective frequency jump may be identified, i.e. Subsequently, due to environmental factors, the signal could not be detected in subsequent frames, resulting in an abnormal situation where the signal frequency transition state switched back to 1. Regarding the spectral overlap effect at the frequency transition moment, when a signal switches from one frequency to another, due to the limitations of FFT time resolution, at the critical moment of frequency switching, a single frame spectrum may exhibit two corresponding frequency peaks. Therefore, the frequency transition state... The moment when the frequency transitions from 2 to 3 or 1 is marked as a coarse estimate of the transition moment; the corresponding frame index is recorded when the frequency transition state frame index meets the following conditions:

[0040] ,

[0041] This allows for the construction of a set of signal frequency hopping frame indices that meet the specified conditions. .

[0042] Among them, the number of signal frequency transitions , Indicates the first Sub-signal frequency jump frame index. This indicates the total number of signal frequency transitions.

[0043] Based on the correspondence between the signal frequency jump frame index and the time, a coarse estimate sequence of jump times is obtained. , among which, the Rough estimate of the time of the next signal frequency jump The calculation is as follows:

[0044] .

[0045] Step 3: Analyze the difference between the coarse estimates of the frequency jump time in Step 2 to obtain the real-time frequency jump period estimation result. Set the effective jump period level, and perform quasi-real-time effective judgment, cumulative averaging and stable level statistics on the real-time results to obtain the stable frequency jump period estimation result. The innovation of this invention is that it adopts a three-layer progressive processing logic of real-time difference, quasi-real-time estimation and stable statistical estimation to achieve adaptive stable estimation of the frequency jump period.

[0046] Step 31: Set the jump cycle level ,in This indicates the number of gears that support adaptive cycle skipping estimation. Each gear has a certain interval, defining the range of the cycle skipping for each gear. .

[0047] Step 32: Subtract the coarse estimate sequence of jump times from Step 26 to obtain the real-time frequency jump period result sequence. , of which Sub-real-time frequency jump cycle estimation results for:

[0048] ,

[0049] in, Indicates the first Rough estimate of the moment when the signal frequency jumps.

[0050] Step 33: Estimate the real-time frequency jump period. After averaging and considering false alarms, missed detections, and jitter at the frequency transition moment, the real-time frequency transition period estimation result is first determined. Is it within any set transition period range? Inside, obtained the first The results of the real-time frequency jump cycle estimation are validly marked. :

[0051] ,

[0052] Set near real-time estimated hop count For each Real-time frequency jump cycle results Perform valid judgments and accumulation to obtain The sum of sub-quasi-real-time frequency jump period estimation results Counting the results of effective real-time frequency jump period estimation Among them, the index of quasi-real-time signal frequency jump period results , For floor operations, the first... The sum of sub-quasi-real-time frequency jump period estimation results The calculation is as follows:

[0053] .

[0054] No. Count of effective real-time frequency jump cycle estimation results The calculation is as follows:

[0055] .

[0056] Based on the summation of the quasi-real-time frequency jump period estimation results Counting the results of effective real-time frequency jump period estimation The quasi-real-time frequency jump period estimation result sequence was calculated. , among which, the Sub-quasi-real-time frequency jump period estimation results The calculation is as follows:

[0057] .

[0058] Step 34: Determine the quasi-real-time frequency jump period estimation result Gear position , among which, the The sub-quasi-real-time frequency jump period estimation result is at the following level: ,satisfy , among which, number .

[0059] Step 35: Set stable hop count estimation For each Sub-quasi-real-time frequency jump period estimation results Perform tiered statistical counting to obtain Statistical results of sub-frequency jump cycle Among them, the jump cycle gear number Index of frequency jump period statistics , No. sequence Statistical results of frequency jump cycle for:

[0060] .

[0061] Step 36: Analyze the statistical results of frequency jump period grading one by one. Take the first The frequency jump cycle statistics result shows that the jump cycle value corresponding to the gear where the peak value is located is the [number]. Substable jump period estimation results ,in, For the first Sub-stable jump cycle gear, satisfying , Thus, a sequence of stable jump period estimation results is obtained. .

[0062] Step 4: Perform initial tracking based on the stable frequency jump period estimation results obtained in Step 3 to obtain the stable reference jump time that satisfies the stable frequency jump period, and generate a stable period tracking window based on this time and the stable jump period estimation results.

[0063] Step 41: Record the time when the initial tracking begins as... Initially, this moment represents the result of the first stable transition period. The effective moment, in subsequent processing, is the moment to restart tracing, initialize the tracing success flag, and set the tracing success flag at this moment. The value is 0; after this moment arrives, a rough estimate is awaited for the first frequency jump moment. ,in for The index of the coarse estimate at the time of the first frequency jump satisfies the following condition:

[0064] ,

[0065] Will The reference jump time for subsequent tracking steps The index of the stable frequency jump period estimation result corresponding to the benchmark jump moment is: From the stable jump period estimation result sequence in step 3 Read the stable frequency jump period corresponding to the index of the stable frequency jump period estimation result, and denot it as . .

[0066] Step 42: Set the initial tracking duration Duration of tracking window The reference jump time obtained in step 41 Starting with the stable transition period corresponding to that moment. Generate an initial periodic tracking window function for the repetition period. :

[0067] ,

[0068] Among them, the sequence of tracking windows , This represents the total number of tracking windows within the initial tracking duration.

[0069] Step 43, Initial tracking duration Internal use of initial periodic tracking window function Coarse estimate sequence of frequency jump moments Perform initial tracking and compile rough estimates of the frequency jump moments tracked within the initial tracking window.

[0070] Specifically, the tracking status of each tracking window is assessed, and the tracking flag for each tracking window is obtained. If the coarse estimate sequence at the frequency jump time There are coarse estimates of the frequency jump moments in the data. Within the range, then 1 if true, 0 otherwise; during the initial tracking duration At the end, count the total number of successful initial tracking attempts. :

[0071] ;

[0072] Considering the issues of false alarm detection and discontinuous bandwidth in frequency hopping signal detection, a tracking success percentage threshold is set. Determine if the initial total number of successful tracking attempts meets the tracking success threshold. Then determine that the tracking was successful and record a tracking success flag. If the result is 1, proceed to step 44; otherwise, return to step 41 to restart the next initial tracking. The innovation of this invention lies in the ability to flexibly configure the tracking success percentage threshold based on the false alarm rate index or the continuity of the frequency hopping signal detection bandwidth. This enables universal tracking across multiple scenarios.

[0073] Step 44: Coarse estimate of the value sequence from the frequency jump time. In the middle of the screening The coarse estimate of the frequency jump time within the time range is used as the stable reference jump time for initial tracking. If there are multiple coarse estimates of frequency jump moments that meet the conditions, to approximate... The frequency jump time at any given moment is roughly estimated.

[0074] Step 45: Using the stable reference jump time obtained in step 44 Starting with Generate a stable periodic tracking window function for the repetition period. :

[0075] ,

[0076] in, To stabilize the start time of the periodic tracking window, To stabilize the end time of the periodic tracking window, For stable tracking window sequence number.

[0077] Step 5: Based on the stable periodic tracking window generated in Step 4, the coarse estimate sequence of frequency jump moments in Step 2 is tracked and filtered in real time to obtain a stable frequency jump moment estimate sequence. At the same time, a dual stable tracking state feedback mechanism is set up to adaptively restart tracking.

[0078] Step 51: Based on the stable periodic tracking window generated in Step 4 The coarse estimate sequence of frequency jump times in step 2 Real-time tracking and filtering are performed. When tracking is unstable, the coarse estimate of the original frequency jump time is directly output. When tracking is stable, the coarse estimate of the original frequency jump time within the stable period tracking window is output. Coarse estimates of the original frequency jump time that do not meet the stable period are filtered out to obtain a sequence of stable frequency jump time estimates. Among them, the estimated value of the stable frequency jump time And it meets the following conditions:

[0079] .

[0080] Step 52: Set up a dual stable tracking state feedback mechanism to monitor the tracking status of the stable period tracking window and the changes in the estimated jump period. The innovation of this invention lies in the fact that, through the dual stable tracking state feedback mechanism, adaptive restart tracking can be achieved, improving the accuracy of frequency jump time estimation. Specifically, within the time range of each stable period tracking window... Estimated time of stable frequency transition during internal monitoring If continuous None of the stable periodic tracking windows detected an event that met the conditions. If the estimated result of the stable frequency jump period in step 3 changes, return to step 4 to restart tracking.

Claims

1. A method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window, characterized in that, The process involves the following steps: First, a coarse estimation of the transition time is performed based on the frequency hopping signal detection results. Then, a stable adaptive estimation of the transition period is performed. A period tracking window is generated based on the stable statistical estimation of the transition period. Finally, the coarsely estimated transition time is filtered out, and the stable frequency transition time estimate of the frequency hopping signal is output. Step 1: Perform spectrum analysis and signal detection on the frequency hopping signal to obtain detection results for multiple consecutive frames, including signal detection markers, signal peak frequency index, signal frequency left boundary index, and signal frequency right boundary index; Step 2: Set a configurable frequency index protection interval, design a latching mechanism for the frequency index of the previous hop valid signal, analyze the signal detection result set obtained in Step 1 frame by frame, and estimate the frequency hopping signal frequency hopping time by analyzing the changes in the signal frequency index, considering the sensitivity environment and the spectral overlap effect at the frequency hopping moment, and obtain a rough estimate sequence of frequency hopping moments. Step 3: Analyze the difference between the coarse estimates of the frequency jump time in Step 2, obtain the real-time frequency jump period estimation result, set the effective jump period level, perform quasi-real-time effective judgment, cumulative average and stable level statistics on the real-time results, obtain the stable frequency jump period estimation result, and realize the adaptive stable estimation of the frequency jump period. Step 4: Based on the stable frequency jump period estimation results obtained in Step 3, perform initial tracking to obtain the stable reference jump time that satisfies the stable frequency jump period, and generate a stable period tracking window based on this time and the stable jump period estimation results. Step 5: Based on the stable periodic tracking window generated in Step 4, the coarse estimate sequence of frequency jump moments in Step 2 is tracked and filtered in real time to obtain a stable frequency jump moment estimate sequence. At the same time, a dual stable tracking state feedback mechanism is set up to adaptively restart tracking.

2. The method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window according to claim 1, characterized in that, In step 1, spectral analysis and signal detection are performed on the frequency hopping signal to obtain detection results for multiple consecutive frames, including signal detection markers, signal peak frequency index, signal frequency left boundary index, and signal frequency right boundary index. Specifically, this includes the following steps: Step 11: Perform digital down-conversion processing on the input frequency-hopping signal. The input frequency-hopping signal is located in the intermediate frequency band. The signal spectrum is shifted to the baseband using quadrature demodulation technology to obtain the baseband equivalent complex signal sequence. ,in, and These are the in-phase and quadrature component sequences of the signal, respectively. The imaginary unit, For discrete-time indexing; Step 12: Process the equivalent complex signal sequence obtained in Step 11. Perform FFT operation, the number of FFT points is By calculating the spectral amplitude of the complex signal, the energy distribution characteristics of the signal in the frequency domain are analyzed, and the signal detection threshold is determined. Step 13: Compare the signal spectral energy with the detection threshold frame by frame, where each... Point operations are performed to obtain a single frame of data, and then the signal detection results for multiple consecutive frames are obtained. ,in, For the total number of frames, the first... Frame detection results It contains the following elements: ， in, Indicates the first Frame signal detection flag: 1 indicates a signal was detected, 0 indicates no signal was detected. Indicates the first Frame signal peak frequency index Indicates the first Frame signal frequency left boundary index, Indicates the first Frame signal frequency right boundary index, frame index Corresponding time ,in, The time for each frame.

3. The method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window according to claim 2, characterized in that, In step 2, a configurable frequency index protection interval is set, a latching mechanism for the frequency index of the previous hop valid signal is designed, and the signal detection result set obtained in step 1 is analyzed frame by frame. By analyzing the changes in the signal frequency index, considering the sensitivity environment and the spectral overlap effect at the frequency hopping moment, the frequency hopping moment of the frequency hopping signal is estimated, and a coarse estimate sequence of frequency hopping moments is obtained. Specifically, the following steps are included: Step 21: Based on the detection bandwidth With actual sampling bandwidth and FFT points Calculate the number of frequency indices outside the detection bandwidth. : ， in, For floor operations, the effective frequency index range is then determined. for ； Step 22: Analyze the detection results frame by frame. , judge the first Frame signal peak frequency index Is it within the effective frequency index range? Inside, obtained the first Frame detection frequency valid marker : ； Step 23: Analyze the detection results frame by frame. Effective markers for detection frequency When the signal detection frequency is valid, the left and right boundary indices of the signal frequency for that frame are latched and updated to obtain the latching result of the left boundary index of the signal frequency. Latch result with right boundary index of signal frequency , specifically: ， ； Step 24: Set the frequency protection interval Frame-by-frame analysis of detection results When the first A frequency transition is determined when the frame signal frequency boundary index meets the following conditions: the left boundary of the signal frequency minus the frequency guard interval is greater than the latched result of the right boundary of the signal frequency index, or the right boundary of the signal frequency plus the frequency guard interval is greater than the latched result of the left boundary of the signal frequency index, thus obtaining the first... Frame frequency jump marker , specifically: ； Step 25: Analyze the detection results frame by frame. Detection frequency valid marker Frequency jump marker Update the frequency transition state of each frame of signal. The state transition rule is: if the first state transition rule is: No signal was detected in the first frame, so the state is 1; if the first frame... If a signal is detected in the frame, but the signal frequency is outside the valid detection range, the state is 0; if the first frame... The frame detects a signal, the signal frequency is within the valid detection range, and the frequency changes; the state is 2. If the first frame detects a signal, the signal frequency is within the valid detection range, and the frequency changes, the state is 2. A frame detects a signal, the signal frequency is within the valid detection range, and the frequency has not changed. The state is 3, i.e.: ； Step 26: Analyze the frequency transition state frame by frame. Considering the sensitivity's environmental adaptability and the spectral overlap effect at the frequency jump moment, a coarse estimate of the frequency jump moment is determined. Specifically, considering the influence of the sensitivity environment, it is possible that an effective frequency jump may be identified, i.e. Subsequently, due to environmental factors, the signal could not be detected in subsequent frames, resulting in an abnormal situation where the signal frequency transition state switched back to 1. Regarding the spectral overlap effect at the frequency transition moment, when a signal switches from one frequency to another, due to the limitations of FFT time resolution, at the critical moment of frequency switching, a single frame spectrum may exhibit two corresponding frequency peaks. Therefore, the frequency transition state... The moment when the frequency transitions from 2 to 3 or 1 is marked as a coarse estimate of the transition moment; the corresponding frame index is recorded when the frequency transition state frame index meets the following conditions: ， This allows for the construction of a set of signal frequency hopping frame indices that meet the specified conditions. Among them, the number of signal frequency transitions , Indicates the first Sub-signal frequency jump frame index. This indicates the total number of signal frequency transitions; Based on the correspondence between the signal frequency jump frame index and the time, a coarse estimate sequence of jump times is obtained. , among which, the Rough estimate of the time of the next signal frequency jump The calculation is as follows: 。 4. The method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window according to claim 3, characterized in that, In step 3, the difference between the coarse estimates of the frequency jump time in step 2 is analyzed to obtain the real-time frequency jump period estimation result. Effective jump period levels are set, and the real-time results are subjected to quasi-real-time effective judgment, cumulative averaging, and stable level statistics to obtain a stable frequency jump period estimation result. This achieves adaptive stable estimation of the frequency jump period, specifically including the following steps: Step 31: Set the jump cycle level ,in This indicates the number of gears that support adaptive cycle skipping estimation. Each gear has a certain interval, defining the range of the cycle skipping for each gear. ; Step 32: Subtract the coarse estimate sequence of jump times from Step 26 to obtain the real-time frequency jump period result sequence. , of which Sub-real-time frequency jump cycle estimation results for: ， in, Indicates the first Rough estimate of the timing of the next signal frequency jump; Step 33: Estimate the real-time frequency jump period. After averaging and considering false alarms, missed detections, and jitter at the frequency transition moment, the real-time frequency transition period estimation result is first determined. Is it within any set transition period range? Inside, obtained the first The results of the real-time frequency jump cycle estimation are validly marked. : ， Set near real-time estimated hop count For each Real-time frequency jump cycle results Perform valid judgments and accumulation to obtain The sum of sub-quasi-real-time frequency jump period estimation results Counting the results of effective real-time frequency jump period estimation Among them, the index of quasi-real-time signal frequency jump period results , For floor operations, the first... The sum of sub-quasi-real-time frequency jump period estimation results Calculated as ， No. Count of effective real-time frequency jump cycle estimation results Calculated as ， Based on the summation of the quasi-real-time frequency jump period estimation results Counting the results of effective real-time frequency jump period estimation The quasi-real-time frequency jump period estimation result sequence was calculated. , among which, the Sub-quasi-real-time frequency jump period estimation results The calculation is as follows: ； Step 34: Determine the quasi-real-time frequency jump period estimation result Gear position , among which, the The sub-quasi-real-time frequency jump period estimation result is at the following level: ,satisfy ,in, ; Step 35: Set stable hop count estimation For each Sub-quasi-real-time frequency jump period estimation results Perform tiered statistical counting to obtain Statistical results of sub-frequency jump cycle Among them, the jump cycle gear number Index of frequency jump period statistics , No. sequence Statistical results of frequency jump cycle for ； Step 36: Analyze the statistical results of frequency jump period grading one by one. Take the first The frequency jump cycle statistics result shows that the jump cycle value corresponding to the gear where the peak value is located is the [number]. Substable jump period estimation results ,in, For the first Sub-stable jump cycle gear, satisfying , Thus, a sequence of stable jump period estimation results is obtained. .

5. The method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window according to claim 4, characterized in that, In step 4, initial tracking is performed based on the stable frequency jump period estimation result obtained in step 3 to obtain the stable reference jump time that satisfies the stable frequency jump period. A stable period tracking window is then generated using this time and the stable jump period estimation result. Specifically, this includes the following steps: Step 41: Record the time when the initial tracking begins as... Initially, this moment represents the result of the first stable transition period. The effective moment, in subsequent processing, is the moment to restart tracing, initialize the tracing success flag, and set the tracing success flag at this moment. The value is 0; after this moment arrives, a rough estimate is awaited for the first frequency jump moment. ,in for The index of the coarse estimate at the time of the first frequency jump satisfies the following condition: ， Will The reference jump time for subsequent tracking steps The index of the stable frequency jump period estimation result corresponding to the benchmark jump moment is: From the stable jump period estimation result sequence in step 3 Read the stable frequency jump period corresponding to the index of the stable frequency jump period estimation result, and denot it as . ; Step 42: Set the initial tracking duration Duration of tracking window The reference jump time obtained in step 41 Starting with the stable transition period corresponding to that moment. Generate an initial periodic tracking window function for the repetition period. : ， Among them, the sequence of tracking windows , This represents the total number of tracking windows within the initial tracking duration. Step 43, Initial tracking duration Internal use of initial periodic tracking window function Coarse estimate sequence of frequency jump moments Perform initial tracking and compile rough estimates of the frequency jump moments tracked within the initial tracking window; Specifically, the tracking status of each tracking window is assessed, and the tracking flag for each tracking window is obtained. If the coarse estimate sequence at the frequency jump time There are coarse estimates of the frequency jump moments in the data. Within the range, then 1 if true, 0 otherwise; during the initial tracking duration At the end, count the total number of successful initial tracking attempts. : ； Considering the issues of false alarm detection and discontinuous bandwidth in frequency hopping signal detection, a tracking success percentage threshold is set. Determine if the initial total number of successful tracking attempts meets the tracking success threshold. Then determine that the tracking was successful and record a tracking success flag. If the result is 1, proceed to step 44; otherwise, return to step 41 and restart the initial tracking. Step 44: Coarse estimate of the value sequence from the frequency jump time. In the middle of the screening The coarse estimate of the frequency jump time within the time range is used as the stable reference jump time for initial tracking. If there are multiple coarse estimates of frequency jump moments that meet the conditions, to approximate... The frequency jump time at any given moment is roughly estimated. Step 45: Using the stable reference jump time obtained in step 44 Starting with Generate a stable periodic tracking window function for the repetition period. : ， in, To stabilize the start time of the periodic tracking window, To stabilize the end time of the periodic tracking window, For stable tracking window sequence number.

6. The method for estimating the stable transition time of a frequency hopping signal based on an adaptive periodic tracking window according to claim 5, characterized in that, In step 5, the coarse estimate sequence of frequency jump moments from step 2 is filtered out in real time based on the stable periodic tracking window generated in step 4 to obtain a stable frequency jump moment estimate sequence. Simultaneously, a dual stable tracking state feedback mechanism is set up to adaptively restart tracking. Specifically, this includes the following steps: Step 51: Based on the stable periodic tracking window generated in Step 4 The coarse estimate sequence of frequency jump times in step 2 Real-time tracking and filtering are performed. When tracking is unstable, the coarse estimate of the original frequency jump time is directly output. When tracking is stable, the coarse estimate of the original frequency jump time within the stable period tracking window is output. Coarse estimates of the original frequency jump time that do not meet the stable period are filtered out to obtain a sequence of stable frequency jump time estimates. Among them, the estimated value of the stable frequency jump time And it meets the following conditions: ； Step 52: Set up a dual stable tracking state feedback mechanism to monitor the tracking status of the stable period tracking window and the changes in the jump period estimate. Specifically, within the time range of each stable period tracking window... Estimated time of stable frequency transition during internal monitoring If continuous None of the stable periodic tracking windows detected an event that met the conditions. If the estimated result of the stable frequency jump period in step 3 changes, return to step 4 to restart tracking.

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