A time domain detection and doppler frequency offset estimation method and device for data link signals

Abstract

The application provides a time domain detection and Doppler frequency offset estimation method and device of a data link signal, relates to the technical field of signal processing, and comprises the following steps: in the process of performing a sliding window detection on an entire real signal data, for each window, performing coarse scanning on a target frequency interval to determine a first frequency point with maximum integral power, performing fine scanning on the frequency corresponding to the first frequency point to determine a second frequency point with maximum integral power, taking the frequency corresponding to the second frequency point as a target peak frequency of the window, and taking the integral power at the second frequency point as a target integral power of the window; determining a current adjacent frequency reference power based on the integral power at the adjacent frequency points of the second frequency point; determining whether the window hits based on the target integral power and the current adjacent frequency reference power; determining a best hit window from a plurality of hit windows and performing frequency offset fine estimation to obtain a final frequency offset. The application can realize low-complexity fast frequency offset estimation and reduce the calculation amount and online time delay.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a method and apparatus for time-domain detection and Doppler frequency offset estimation of data link signals. Background Technology

[0002] Link-11 is characterized by its use of analog audio channels to transmit voice and data, and it can operate in both HF (High Frequency) and UHF (Ultra High Frequency) bands. Link-11 has a relatively low data transmission rate and lacks interference immunity; however, it can use the HF band and has cross-horizon communication capabilities. Link-11A is a mesh half-duplex data link that uses CLEW (Conventional Link Eleven Waveform) for data exchange, employing a parallel transmission system and standard information format. Its modulation method is π / 4-DQPSK (Differential Quadrature Phase Shift Keying), using multiple single-tone parallel bearers and differential phase modulation to form frame-based data in the baseband.

[0003] Currently, the commonly used method is the grid FFT (Fast Fourier Transform) / spectral method, which uses high-resolution FFT to scan the energy peaks near the nominal frequency f0 and sets a fixed threshold for detection; or the STFT (Short-Time Fourier Transform) is used to find local peaks on the time-frequency plane using a time-spectrum graph.

[0004] However, although the above scheme is simple to implement, it requires thousands of FFTs to achieve a resolution of ≤10Hz, which brings significant computation and caching latency, resulting in high computational complexity and latency. Summary of the Invention

[0005] This invention provides a time-domain detection and Doppler frequency offset estimation method and apparatus for data link signals, which solves the problems of high computational complexity and time delay when using the grid FFT / spectral method to obtain a resolution of ≤10Hz in the prior art. It achieves fast frequency offset estimation with low complexity, reducing the amount of computation and online delay.

[0006] This invention provides a method for time-domain detection and Doppler frequency offset estimation of data link signals, comprising:

[0007] During the sliding window detection process on the entire real signal data, for each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integrated power, and a fine scan is performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integrated power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window, and the integrated power at the second frequency point is taken as the target integrated power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range.

[0008] Based on the integrated power at the adjacent frequency point of the second frequency point, determine the current adjacent frequency reference power;

[0009] Based on the target integrated power and the current adjacent frequency reference power, it is determined whether the window has been hit;

[0010] The optimal hit window is determined from multiple hit windows, and the frequency offset is precisely estimated within the optimal hit window to obtain the final frequency offset.

[0011] According to the present invention, a time-domain detection and Doppler frequency offset estimation method for data link signals is provided, wherein determining whether the window is hit based on the target integrated power and the current adjacent frequency reference power includes:

[0012] Obtain the current noise reference;

[0013] Calculate the target / noise ratio based on the target integrated power and the current noise reference;

[0014] Calculate the target / adjacent channel power ratio based on the target integrated power and the current adjacent channel reference power;

[0015] A window that simultaneously satisfies the first hit decision condition and the second hit decision condition is determined as a hit window; the first hit decision condition is that the target / noise ratio is greater than or equal to a first set threshold, and the second hit decision condition is that the target / adjacent channel power ratio is greater than or equal to a second set threshold.

[0016] According to the present invention, a method for time-domain detection and Doppler frequency offset estimation of data link signals is provided, wherein obtaining the current noise reference includes:

[0017] Obtain the currently maintained noise ring queue; the noise ring queue is used to store historical adjacent frequency reference power;

[0018] If the length of the noise loop queue is less than a preset length threshold, then the current adjacent frequency reference power of the window is used as the current noise reference.

[0019] If the length of the noise ring queue is greater than or equal to a preset length threshold, then the median of the noise ring queue is used as the current noise benchmark.

[0020] According to the present invention, a method for time-domain detection and Doppler frequency offset estimation of a data link signal, wherein determining the optimal hit window from multiple hit windows includes:

[0021] If the window is determined to be a hit window, the information of the window is recorded in the consecutive hit sequence, and the consecutive hit count is incremented by one;

[0022] If the window is determined to be a missed window, the information in the consecutive hit sequence is cleared and the consecutive hit count is reset to zero.

[0023] When the number of consecutive hits reaches a preset number, the hit window with the largest target / noise ratio is selected from multiple hit windows recorded in the consecutive hit sequence as the best hit window.

[0024] According to the present invention, a method for time-domain detection and Doppler frequency offset estimation of a data link signal is provided, wherein the step of performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset includes:

[0025] Within the optimal hit window, the target peak frequency of the optimal hit window is used as the down-conversion frequency to move the signal data segment to the baseband.

[0026] Short-time mean smoothing is performed with a preset moving average length, complex correlation is performed with a preset number of L1 samples, and the residual frequency is estimated based on the phase increment.

[0027] The final frequency offset is determined based on the residual frequency, the target peak frequency of the optimal hit window, and the nominal frequency.

[0028] According to the present invention, a time-domain detection and Doppler frequency offset estimation method for data link signals, after performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset, further includes:

[0029] If signal detection is successful, the following information is output: detection status, final frequency offset, preamble start point, sliding window start point of the optimal hit window, target peak frequency of the optimal hit window, target / noise ratio and target / adjacent channel power ratio of the optimal hit window; wherein, the sliding window start point is the starting sampling point position of the optimal hit window in the entire real signal data, and the preamble start point is obtained by backtracking backward based on the sliding window start point;

[0030] If the preset number of windows are not hit consecutively by the end of the window traversal, the system returns to the "not found" state.

[0031] The present invention also provides a time-domain detection and Doppler frequency offset estimation device for data link signals, comprising:

[0032] The coarse and fine scan modules are used to perform sliding window detection on the entire segment of real signal data. For each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integrated power. A fine scan is then performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integrated power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window, and the integrated power at the second frequency point is taken as the target integrated power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range.

[0033] The adjacent frequency reference power determination module is used to determine the current adjacent frequency reference power based on the integrated power at the adjacent frequency point of the second frequency point;

[0034] The hit determination module is used to determine whether the window has been hit based on the target integrated power and the current adjacent frequency reference power;

[0035] The frequency offset fine estimation module is used to determine the best hit window from multiple hit windows, and perform frequency offset fine estimation within the best hit window to obtain the final frequency offset.

[0036] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the time-domain detection and Doppler frequency offset estimation method for the data link signal as described above.

[0037] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the time-domain detection and Doppler frequency offset estimation method for data link signals as described above.

[0038] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the time-domain detection and Doppler frequency offset estimation method for data link signals as described above.

[0039] This invention provides a time-domain detection and Doppler frequency offset estimation method and apparatus for data link signals. During the sliding window detection process across the entire real signal data segment, a target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range. For each window, a coarse scan is performed within the target frequency range to determine the first frequency point with the maximum integrated power. A fine scan is then performed, centered on the frequency corresponding to the first frequency point, to determine the second frequency point with the maximum integrated power. This achieves a two-stage search of coarse and fine scans, utilizing a finite-frequency time-domain Discrete Fourier Transform (DFT). The Discrete Fourier Transform (DFT) integral replaces the large-point-count FFT, considering the maximum Doppler frequency shift range. It can cover a wide frequency offset and achieve high-resolution micro-scanning near the peak. The coarse time-domain synchronization point can be used as the starting point for subsequent fine time-domain synchronization, thus achieving more accurate time-domain fine synchronization within a smaller time-domain range, without having to perform time-domain fine synchronization on the entire data segment, achieving robust acquisition under wide frequency offset conditions. By using the frequency corresponding to the second frequency point as the target peak frequency of the window and the integral power at the second frequency point as the target integral power of the window, the current adjacent frequency reference power is determined based on the integral power at the adjacent frequency point of the second frequency point. The window hit is determined based on the target integral power and the current adjacent frequency reference power. The optimal hit window is determined from multiple hit windows, and the final frequency offset is obtained by fine frequency offset estimation within the optimal hit window. Thus, time-domain detection and fine frequency offset estimation can be completed without performing a large-point FFT, achieving fast frequency offset estimation with low complexity, reducing computational load and online latency. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is one of the flowcharts illustrating a time-domain detection and Doppler frequency offset estimation method for a data link signal provided in an embodiment of the present invention.

[0042] Figure 2 This is the second flowchart of a method for time-domain detection and Doppler frequency offset estimation of data link signals provided in an embodiment of the present invention.

[0043] Figure 3 This is a time-domain waveform diagram of the generated preamble real signal provided in an embodiment of the present invention.

[0044] Figure 4This is a comparison chart of detection probability results provided in an embodiment of the present invention.

[0045] Figure 5 This is a comparison chart of false alarm probability results provided in an embodiment of the present invention.

[0046] Figure 6 This is a comparison chart of the frequency offset estimation accuracy provided in the embodiments of the present invention.

[0047] Figure 7 This is a schematic diagram of the structure of a time-domain detection and Doppler frequency offset estimation device for a data link signal provided in an embodiment of the present invention.

[0048] Figure 8 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0050] In the description of embodiments of the present invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Those skilled in the art will understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0051] The following is a brief overview of the protocol's key points. The Link-11 CLEW preamble consists of two tones at frequencies of 605Hz and 2915Hz. The 605Hz tone is a Doppler tone used to correct for Doppler shifts caused by relative motion of the terminal equipment or changes in the high-frequency channel; its phase remains continuous throughout the preamble transmission. The 2915Hz tone is a synchronization tone, modulated using BPSK (Binary Phase Shift Keying), with a 180° phase transition at the end of each frame for synchronization at the receiver. The preamble lasts for 5 frames, or 66.65ms if a fast transmission rate is used, and is transmitted at four times the normal power. Under normal conditions, the transmit power of data frames (excluding 605Hz) is 0dB, and the transmit power of 605Hz is 6dB. In the preamble, the transmit power of 605Hz is 12dB, and the transmit power of 2915Hz is 6dB.

[0052] Figure 1 This is one of the flowcharts illustrating a time-domain detection and Doppler frequency offset estimation method for data link signals provided in an embodiment of the present invention. (Refer to...) Figure 1 This invention provides a method for time-domain detection and Doppler frequency offset estimation of data link signals, which specifically includes the following steps:

[0053] Step 101: During the sliding window detection process on the entire real signal data, for each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integrated power, and a fine scan is performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integrated power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window, and the integrated power at the second frequency point is taken as the target integrated power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range.

[0054] It should be noted that the execution subject of the time-domain detection and Doppler frequency offset estimation method for data link signals provided in this embodiment of the invention can be an electronic device, a component in the electronic device, an integrated circuit, or a chip. The electronic device can be a mobile electronic device or a non-mobile electronic device. For example, a mobile electronic device can be a mobile phone, tablet computer, laptop computer, PDA, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc., while a non-mobile electronic device can be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This embodiment of the invention does not specifically limit the specific implementation of these devices. The following embodiments of the invention describe the execution subject using a server as the execution subject.

[0055] A data link signal can refer to a communication signal used to transmit formatted digital information according to a specific message format and communication protocol. In this embodiment of the invention, the data link signal can specifically be a Link-11 CLEW signal.

[0056] A complete real signal data segment can refer to the raw time-domain sampled sequence output by a receiving device (such as a data link terminal or software receiver), without any truncation or segmentation processing, and represented in real number form. A complete real signal data segment typically includes long periods of background noise, interference, and burst signal pulses that may occur at any time.

[0057] In some embodiments, the detection step size can be used to sequentially slide across the entire real signal data segment. After each slide, if the current window interval has not exceeded the limit, a data segment of length equal to the window length can be taken and multiplied by the Hann window to obtain the segment to be detected (i.e., the window), thereby enabling the detection of each segment to be detected. Does the target signal exist (i.e., does the Link-11 CLEW signal exist)?

[0058] In some embodiments, before performing sliding window detection on the entire real signal data segment, a Hann window can be generated in advance and stored for later retrieval. The formula for the Hann window can be:

[0059] ;

[0060] The formula for adding a window can be:

[0061] ;

[0062] Where n is the index of the time-domain sample point. L is the data length of a single scan; It is the Hann window corresponding to the time-domain sample n; It is a segment of signal data within the window; It is a signal data segment obtained by windowing.

[0063] The embodiments of the present invention perform sliding window detection on the entire real signal data, which can transform long-term entire real signal data into short-term stable data segments of finite length that can be analyzed in the frequency domain, thus facilitating subsequent coarse and fine frequency scanning processing.

[0064] In this embodiment of the invention, sliding window detection can be performed on the entire segment of real signal data. Within each window, a coarse scan can be performed first on the target frequency range to find the first frequency point with the largest integrated power. Then, a fine scan can be performed centered on the first frequency point with the largest integrated power to find the second frequency point with the largest integrated power. The frequency corresponding to the second frequency point is then used as the target peak frequency (i.e., the precise peak frequency) of the current window. The integrated power at the second frequency point is taken as the target integrated power corresponding to the target peak frequency of the current window. .

[0065] In some embodiments, the target frequency range may be ;in, It is the nominal frequency, and Span is the maximum Doppler shift range.

[0066] In some embodiments, the target frequency range can be... The above constructs a set of coarse sweep frequency points in frequency domain coarse sweep steps, calculates the integrated power for each coarse sweep frequency point, and takes the frequency corresponding to the maximum value as the center frequency. The formula for constructing the coarse sweep frequency point set can be as follows:

[0067] ;

[0068] in, For frequency domain coarse sweep step; is the frequency interval between two coarse sweep frequency points; k is the frequency point number; It is the nominal frequency; Span is the maximum Doppler shift range; It is the frequency corresponding to the kth coarse sweep frequency point.

[0069] This invention constructs a set of coarse sweep frequency points in frequency domain coarse sweep steps within a target frequency range determined based on the nominal frequency and the maximum Doppler frequency shift range. It calculates the integrated power at each coarse sweep frequency point in the set and determines the coarse sweep frequency point with the largest integrated power as the first frequency point. This allows the rough time-domain synchronization point to be used as the starting point for subsequent time-domain fine synchronization, facilitating more accurate time-domain fine synchronization within a smaller time domain range, without having to perform time-domain fine synchronization continuously on the entire data segment.

[0070] In some embodiments, the frequency can correspond to the first frequency point. Centered on a central point, fine scanning frequency points are uniformly set within the frequency domain fine scanning span, and the integrated power at each fine scanning frequency point is calculated. The formula for constructing the set of fine scanning frequency points can be as follows:

[0071] ;

[0072] in, This refers to the frequency domain fine-scan span (i.e., the range of fine scanning). k is the number of fine-scan frequency points; k is the frequency point number. The frequency corresponding to the first frequency point where the integrated power is maximum; This is the frequency corresponding to the kth fine-scan frequency point.

[0073] This invention constructs a set of fine-scan frequency points within the frequency domain fine-scan span, centered on the first frequency point with the highest integrated power determined during coarse scanning. It calculates the integrated power at each fine-scan frequency point in the set and determines the fine-scan frequency point with the highest integrated power as the second frequency point. This allows the coarse time-domain synchronization point to be used as the starting point for subsequent fine time-domain synchronization, enabling more precise fine time-domain synchronization within a smaller time domain range, without having to perform fine time-domain synchronization continuously for the entire data segment.

[0074] In some embodiments, the formula for calculating the integral power at a single frequency point can be as follows:

[0075] ;

[0076] ;

[0077] in, It is the sampling rate; n is the index of the time-domain sample point. L is the data length of a single scan; f is the frequency corresponding to the frequency point; j is the imaginary unit; It is a signal data segment obtained by windowing; It is the integrated power at a single frequency point; It is a windowed signal data segment The spectral values ​​at continuous frequencies f.

[0078] Step 102: Determine the current adjacent frequency reference power based on the integrated power at the adjacent frequency point of the second frequency point.

[0079] In some embodiments, within each window, the single-point integrated power of the two adjacent frequency points of the second frequency point can be calculated separately and averaged to serve as the current adjacent frequency reference power. The formula for calculating the adjacent-channel reference power can be as follows:

[0080] ;

[0081] in, The target peak frequency (i.e., the frequency corresponding to the second frequency point); Frequency resolution; The frequency corresponding to the left neighbor of the second frequency point. This represents the integrated power at the left adjacent frequency point; The frequency corresponding to the right neighbor of the second frequency point. This represents the integrated power at the right adjacent frequency. This is the adjacent-channel reference power.

[0082] Step 103: Based on the target integrated power and the current adjacent frequency reference power, determine whether the window has been hit.

[0083] In some embodiments, after determining the current adjacent channel reference power of the current window, the current adjacent channel reference power can be... Add the noise loop to the queue, and keep the length of the noise loop queue no more than 50.

[0084] In some embodiments, within each window, the target / noise ratio can be calculated based on the target integrated power and the median of the current noise ring queue to determine whether the first hit decision condition is met; the target / adjacent channel power ratio can be calculated based on the target integrated power and the current adjacent channel reference power to determine whether the second hit decision condition is met. If both the first and second hit decision conditions are met, the current window can be determined as a hit window.

[0085] Compared to traditional solutions that rely solely on the target / noise ratio to determine a hit, lacking the ability to suppress leakage or narrowband interference from adjacent frequencies, this invention determines the current window as a hit window only when both the target / noise ratio and the target / adjacent frequency power ratio simultaneously meet the corresponding hit determination conditions. This significantly helps to suppress false alarms caused by leakage and narrowband interference.

[0086] In other embodiments, within each window, the target / adjacent-channel power ratio can be calculated based on the target integrated power and the current adjacent-channel reference power. If the target / adjacent-channel power ratio meets the hit decision criteria, the current window can be determined as a hit window.

[0087] Step 104: Determine the optimal hit window from multiple hit windows, and perform a fine frequency offset estimation within the optimal hit window to obtain the final frequency offset.

[0088] In some embodiments, an optimal hit window can be determined from multiple hit windows. Within the optimal hit window, the signal is down-converted to its peak frequency and subjected to short-time mean smoothing. The residual frequency offset is estimated using the complex correlation phase with a lag of L1 points, and then superimposed. The final CFO (Carrier Frequency Offset) estimate is obtained.

[0089] This invention, through a sliding window detection process on a full segment of real signal data, determines the target frequency range based on the nominal frequency and the maximum Doppler frequency shift range. For each window, a coarse scan is performed within the target frequency range to determine the first frequency point with the maximum integrated power. A fine scan is then performed, centered on the frequency corresponding to the first frequency point, to determine the second frequency point with the maximum integrated power. This achieves a two-stage search of coarse and fine scans. It replaces a large-point FFT with a time-domain DFT integration using a finite-frequency-point approach, considering the maximum Doppler frequency shift range. This allows for coverage of a wide frequency offset (e.g., ±150Hz) and high-resolution micro-scanning near the peak value. The coarse time-domain synchronization point can then serve as the starting point for subsequent fine time-domain synchronization, enabling more precise time-domain synchronization within a smaller time-domain range, without the need for... The system continuously performs time-domain fine synchronization on the entire data segment to achieve robust acquisition under wide frequency offset conditions. By using the frequency corresponding to the second frequency point as the target peak frequency of the window and the integrated power at the second frequency point as the target integrated power of the window, the system determines the current adjacent frequency reference power based on the integrated power at the adjacent frequency point of the second frequency point. Based on the target integrated power and the current adjacent frequency reference power, the system determines whether the window is hit. The system selects the optimal hit window from multiple hit windows and performs fine frequency offset estimation within the optimal hit window to obtain the final frequency offset. Thus, time-domain detection and fine frequency offset estimation can be completed without performing large-point FFT, achieving fast frequency offset estimation with low complexity, reducing computational load and online latency.

[0090] Based on any of the above embodiments, determining whether the window is hit based on the target integrated power and the current adjacent channel reference power includes: obtaining a current noise reference; calculating the target / noise ratio based on the target integrated power and the current noise reference; calculating the target / adjacent channel power ratio based on the target integrated power and the current adjacent channel reference power; determining the window that simultaneously satisfies the first hit decision condition and the second hit decision condition as the hit window; the first hit decision condition is that the target / noise ratio is greater than or equal to a first preset threshold, and the second hit decision condition is that the target / adjacent channel power ratio is greater than or equal to a second preset threshold.

[0091] A noise reference can refer to a value used to represent the average power level of the current background noise. In some embodiments, the median of a noise loop queue can be selected as the noise reference, thereby providing a robust, adaptive noise reference that is resistant to sudden disturbances. .

[0092] In some embodiments, the target integrated power can be converted into a corresponding dB value, and the adjacent frequency reference power can be converted into a corresponding dB value, thereby determining the hit rate based on the dB value. The formula for converting the integrated power of a single frequency point into a dB value can be as follows:

[0093] ;

[0094] in, It is the frequency-integrated power; yes The corresponding dB value.

[0095] The formula for calculating long-term noise (median noise loop) in dB can be as follows:

[0096] ;

[0097] in, Adjacent-channel reference power The corresponding dB value; The m-th record in the noise ring queue ; noise reference The corresponding dB value can degenerate to [value] when the sample size is insufficient. .

[0098] In some embodiments, the target / noise signal-to-noise ratio (The unit is dB) can be calculated using the following formula:

[0099] ;

[0100] in, This represents the dB value corresponding to the target integral power. noise reference The corresponding dB value, The target / noise signal-to-noise ratio.

[0101] Target / Adjacent Channel Power Ratio (The unit is dB) can be calculated using the following formula:

[0102] ;

[0103] in, This represents the dB value corresponding to the target integral power. Adjacent-channel reference power The corresponding dB value, The target / adjacent channel power ratio.

[0104] In this embodiment of the invention, in the current window, if simultaneously satisfying... ≥ First set threshold and If the second threshold is set, the current window can be considered "hit".

[0105] Compared to the traditional approach that uses a single criterion threshold, i.e., only the target-to-noise ratio (SNR) to determine the hit window, which lacks suppression of leakage or narrowband interference at adjacent frequencies, and easily misinterprets adjacent frequency leakage or narrowband interference as target peaks, resulting in high false alarm rates, this invention calculates the target-to-noise ratio and the target-to-adjacent frequency power ratio. Only when both simultaneously meet the corresponding hit decision conditions is the current window determined as a hit window, which is beneficial for significantly suppressing false alarms caused by leakage and narrowband interference.

[0106] Based on any of the above embodiments, obtaining the current noise reference includes: obtaining the currently maintained noise ring queue; the noise ring queue is used to store historical adjacent frequency reference power; if the length of the noise ring queue is less than a preset length threshold, the current adjacent frequency reference power of the window is used as the current noise reference; if the length of the noise ring queue is greater than or equal to the preset length threshold, the median of the noise ring queue is used as the current noise reference.

[0107] In some embodiments, in calculation The power is integrated at a single point and averaged to serve as the adjacent frequency reference power. Then, the currently maintained noise ring queue can be obtained.

[0108] The noise loop queue is a dynamically updated cache of historical observations that stores adjacent-channel reference power from multiple recent windows, used to dynamically maintain the set of noise power observations over a recent period. This embodiment of the invention provides a robust, adaptive noise benchmark that can withstand sudden disturbances by selecting the median of the noise loop queue as the current noise benchmark. .

[0109] In some embodiments, if the length of the noise loop queue is less than a preset length threshold (e.g., less than 8), indicating insufficient samples, the current adjacent frequency reference power can be... As the current noise benchmark (As temporary noise); if the length of the noise ring queue is greater than or equal to a preset length threshold, the median of the noise ring queue can be selected as the current noise benchmark. (As long-term noise).

[0110] In some embodiments, the current adjacent-channel reference power can be added to the noise ring queue (or the dB value corresponding to the current adjacent-channel reference power can be added to the noise ring queue) to achieve dynamic updating of the noise ring queue and control the length of the updated noise ring queue to not exceed a preset upper limit threshold (e.g., 50). Compared with traditional schemes that lack adaptability and where fixed thresholds are difficult to cope with non-stationary noise or changes in channel conditions, this embodiment of the invention achieves low false alarm adaptive decision (CFAR, Constant False Alarm Rate) by dynamically updating the noise ring queue and selecting the median of the noise ring queue to obtain an adaptive threshold. This solves the problem of false alarms easily occurring under non-stationary noise or narrowband interference with fixed thresholds and single energy criteria, requiring the threshold to adapt to environmental changes and effectively suppress false alarm triggering.

[0111] Based on any of the above embodiments, determining the optimal hit window from multiple hit windows includes: if the window is determined to be a hit window, then the information of the window is recorded in the continuous hit sequence and the continuous hit count is incremented by one; if the window is determined to be a miss window, then the information in the continuous hit sequence is cleared and the continuous hit count is reset to zero; when the continuous hit count reaches a preset number, the hit window with the largest target / noise ratio is selected from the multiple hit windows recorded in the continuous hit sequence as the optimal hit window.

[0112] In this embodiment of the invention, when the number of consecutive hits reaches K (i.e., when K hit windows are obtained consecutively), the signal detection is confirmed as successful and the sliding window loop ends. The best hit window is then selected from the K hit windows. Compared to the traditional approach of determining a hit only once, where a single hit is considered a signal detection without confirming consecutive hits, this embodiment of the invention determines a signal detection only when the number of consecutive hits reaches K, which is beneficial for filtering out sporadic triggers.

[0113] In some embodiments, in the current window, if both conditions are met... ≥ First set threshold and If the second threshold is set, the current window can be considered a "hit," and the starting point of the hit window and two metrics (i.e., ...) can be set. and )and The information is recorded into the consecutive hit sequence, and the consecutive hit count is incremented by one. If in the current window, <First set threshold or If the threshold is less than the second set threshold, the consecutive hit sequence is cleared and the consecutive hit count is reset to zero. When the consecutive hit count reaches K, the signal detection is confirmed as successful and the sliding window loop ends. The value of K can be set according to actual needs.

[0114] In some embodiments, the starting point for each sliding window recording can be idx0, and idx0 can be recorded when a hit occurs. After satisfying the condition of "K consecutive hits", a selection can be made from K (or more) hit records. The largest hit window is the optimal hit window.

[0115] This invention embodiment records the SNR / NNR of each hit window and finally selects the one with the highest SNR (or The highest value is used as the optimal hit window, and the starting point and peak frequency are output, thus realizing quality measurement and optimal window selection.

[0116] Based on any of the above embodiments, the step of performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset includes: within the optimal hit window, using the target peak frequency of the optimal hit window as the down-conversion frequency, shifting the signal data segment to the baseband; performing short-time mean smoothing with a preset moving average length, performing complex correlation with a lag of a preset number L1 samples, and estimating the residual frequency based on the phase increment; and determining the final frequency offset based on the residual frequency, the target peak frequency of the optimal hit window, and the nominal frequency.

[0117] In some embodiments, the original data segment of the optimal hit window can be taken, with the target peak frequency of the optimal hit window as the target peak frequency. As the down-conversion frequency, the signal data segment is shifted to baseband, and a slight smoothing is performed with a preset moving average length (e.g., 2ms) to reduce noise phase jitter. A complex correlation with a lag of L1 samples is performed, and the phase increment is taken to obtain the residual frequency component. With residual frequency Add them together to get the relative nominal frequency. Final frequency offset estimation .

[0118] The formula for down-converting to the peak frequency can be as follows:

[0119] ;

[0120] in, It is the original signal data segment within the optimal hit window; It is the sampling rate; n is the index of the time-domain sample point. L is the data length of a single scan; It is the target peak frequency; j is the imaginary unit; It is a complex exponential sequence generated by a digitally controlled oscillator, used to cancel out the carrier frequency component present in the signal; It is the baseband complex signal after down-conversion, used to represent the result of shifting the original signal data segment to baseband (zero frequency).

[0121] The formula for moving average smoothing can be as follows:

[0122] ;

[0123] Where n is the index of the time-domain sample point. L is the data length of a single scan; m is the delay. For example, n-1 refers to the time-domain sample point preceding time-domain sample point n; It is a delayed baseband signal; It is the smoothed baseband signal, through An M-point moving average is performed to obtain the smoothed baseband signal. This embodiment of the invention uses moving average smoothing to suppress out-of-band noise and high-frequency noise in the down-converted baseband signal; through cumulative averaging, relevant signal components can be enhanced, while random noise can be partially canceled.

[0124] The formula for the summation of multiple correlations with lag L1 can be as follows:

[0125] ;

[0126] in, L1 is the smoothed baseband signal; L1 is the number of samples with correlation hysteresis. The larger L1 is, the more sensitive it is to small frequency offsets, but the smaller the estimation range. It is the maximum possible lag value; yes The complex conjugate; This is the complex correlation value, which contains information about the phase change of the signal over time intervals of L1 samples. In this embodiment of the invention, by accumulating the complex correlation with a lag of L1, random noise is averaged out, while the deterministic phase rotation caused by frequency offset is enhanced, making the frequency offset estimation more robust and thus improving the signal-to-noise ratio.

[0127] The formula for residual frequency estimation can be as follows:

[0128] ;

[0129] in, It is the phase angle of the complex correlation value (in radians), representing the total phase rotation of the signal accumulated over the time interval of L1 samples; It is the actual time interval corresponding to the L1 sample points lagging behind; Used to convert actual time intervals into radians; It was estimated. The residual frequency offset (i.e., residual frequency) is estimated using a formula for residual frequency estimation, which allows for the conversion from phase difference to frequency difference.

[0130] Final frequency offset (relative to nominal frequency) The formula for calculating () can be as follows:

[0131] ;

[0132] in, It is the nominal frequency; It is the peak frequency of the target within the optimal hit window; It is the residual frequency; It is the estimated final frequency offset.

[0133] Traditional CFO estimation relies on high-resolution spectra, typically based on peak interpolation or long-time phase expansion, which involves large computational loads and is sensitive to window and resolution.

[0134] Compared to the spectral interpolation method, which is prone to distortion under low SNR, short window, or large frequency offset, and has insufficient robustness in CFO estimation, the embodiments of the present invention use the phase increment method of hysteresis correlation to accurately estimate the residual frequency offset after downconverting to the peak frequency within the optimal hit window. This eliminates the need for spectral interpolation, has extremely low computational load, and achieves lightweight differential phase CFO estimation.

[0135] Based on any of the above embodiments, after performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset, the method further includes: if signal detection is successful, outputting the discovery status, the final frequency offset, the leading start point, the sliding window starting point of the optimal hit window, the target peak frequency of the optimal hit window, the target / noise ratio and the target / adjacent channel power ratio of the optimal hit window; wherein, the sliding window starting point is the starting sampling point position of the optimal hit window in the entire real signal data, and the leading start point is obtained by backtracking backward based on the sliding window starting point; if a preset number of windows are not continuously hit at the end of the window traversal, the method returns to the undiscovered status.

[0136] The starting point of the optimal hit window can refer to the initial sampling point position of the optimal hit window within the entire real signal data segment. The leading starting point refers to the final starting sampling point position determined after protection backtracking.

[0137] In some embodiments, after determining the optimal hit window, the sliding window start point idx of the optimal hit window can be determined as the hit start point hit_win_start, and its start point sample can be traced back to GuardPre as the final leading segment start point (i.e., leading start point) to avoid cutting the leading edge. The formula for start point protection backtracking can be as follows:

[0138] ;

[0139] in, It is the starting point of the hit; It is a forward backtracking protection interval; It is the starting point.

[0140] In this embodiment of the invention, if the detection is successful, the discovery status (i.e., the FOUND status) and the final frequency offset can be output. The leading start point (start_idx), the sliding window start point of the optimal hit window, and the target peak frequency of the optimal hit window. and two quality metrics ( / If the consecutive hit condition is not met after the traversal ends, the Not Found state (NOT_FOUND) can be output, and each result can be set to NaN / empty.

[0141] To enable those skilled in the art to better understand the embodiments of the present invention, the embodiments of the present invention will be described below through a specific example.

[0142] This scheme performs sliding window detection on the entire real signal segment, first performing a coarse scan within each window. The maximum power point is located on the grid, where the span represents the largest Doppler shift range. A fine scan (a set of micro-frequency points within a narrow range) is then performed centered on this point to obtain the precise peak frequency. The adjacent frequency energy (peak ± Δf) is then calculated and combined with the median ring of historical noise to obtain an adaptive noise threshold. A dual-threshold decision is then made using both SNR and NNR, requiring K consecutive hits to confirm successful detection. The window with the highest SNR in the confirmed hit sequence is selected as the "optimal hit window," with the starting point of the corresponding hit window being a coarse time-domain synchronization point. Within the optimal hit window, the signal is down-converted to the peak frequency and subjected to short-time mean smoothing. The residual frequency offset is estimated using the complex correlation phase with a lag of L1 points, and then superimposed. The final CFO estimate is obtained. The output includes the FOUND / NOT_FOUND status, frequency offset, leading start point, detection quality metric, and peak frequency. This rough time-domain synchronization point can serve as the starting point for subsequent fine-tuning in the time domain. More precise fine-tuning can then be performed within a smaller time-domain range, eliminating the need for continuous fine-tuning across the entire data segment.

[0143] Figure 2 This is the second schematic flowchart of a method for time-domain detection and Doppler frequency offset estimation of data link signals provided in an embodiment of the present invention. (Refer to...) Figure 2 In one specific embodiment, this invention provides a method for time-domain detection and Doppler frequency offset estimation of data link signals, the method specifically including the following steps:

[0144] Step 1: Parameter parsing and default configuration.

[0145] (1) Input is a whole segment of real signal Sampling rate nominal frequency (The frequency point used for Doppler estimation by Link-11 CLEW is 605Hz).

[0146] (2) Set the Name-Value parameter of the parsed result structure and set the default value:

[0147] Set the following parameters: time-domain scan window length (recommended value: 26.6ms), time-domain scan step size (recommended value: 10ms), frequency domain coarse scan span (recommended value: 300Hz), frequency domain coarse scan step size (recommended value: 10Hz), frequency domain fine scan span (recommended value: 16Hz), number of frequency domain fine scan micro-frequency points (recommended value: 9), adjacent frequency offset Δf (recommended value: 40Hz), SNR threshold (recommended value: 10dB), NNR threshold (recommended value: 6dB), number of consecutive hits K (recommended value: 3), CFO hysteresis length L1 (recommended value: 8), and hit backtracking length GuardPre (recommended value: 1.3ms).

[0148] (3) Generate the Hann window in one go and store it for later use. Construct a fine-scan micro-frequency point grid (an odd number of points to ensure center alignment) and initialize the noise median ring (up to 50 rings).

[0149] The embodiments of the present invention can be applied to typical audio intermediate frequency sampling with Fs = 8–48 kHz, and the target Doppler frequency offset coverage range can be extended to ±250 Hz.

[0150] Step 2: Sliding window traversal and segmented windowing.

[0151] The detection is performed using a time-domain step size. When the window interval does not exceed the limit, a data segment with a length equal to the window length is taken and multiplied by the Hann window to obtain the segment to be detected.

[0152] Step 3: Coarse scan peak positioning.

[0153] exist The frequency set is constructed using coarse-step frequency domain operations. The integrated power is calculated for each frequency point, and the frequency corresponding to the maximum value is taken as the center frequency. .

[0154] Step 4: Fine scanning.

[0155] by Fine scanning frequencies are uniformly set within the ±fine scanning span centered on the target frequency, and the integrated power of each frequency is calculated. The frequency with the highest power is selected as the target peak frequency for the current window. and corresponding target integral power .

[0156] Step 5: Estimation of adjacent channel power and long-term noise.

[0157] calculate The power is integrated at a single point and averaged to serve as the adjacent frequency reference power. If the noise loop length is less than 8, then... Use the noise ring median as the temporary noise; otherwise, use the noise ring median as the long-term noise. The current Add a loop, keeping the length no more than 50.

[0158] Step 6: Dual-judgment and consecutive hit control.

[0159] Calculate the target / noise ratio Target / Adjacent Channel Power Ratio (Units are all dB). If both SNR ≥ the set threshold and NNR ≥ the set threshold are met simultaneously, it is judged as a "hit", and the starting point of the hit window and the two metrics ( / )and Record the hit sequence; otherwise, clear the hit sequence and reset the consecutive hit count to zero; when the consecutive hit count reaches K times, confirm the detection is successful and end the sliding window loop.

[0160] Step 7: Optimal hit window selection and starting point protection.

[0161] Each time a window slides, the starting point of the slide is recorded as idx0. When a hit occurs, idx0 is recorded. Once the condition of "K consecutive hits" is met, a selection is made from these K (or more) hit records. The largest line is taken as the optimal hit window, and its idx is considered the hit start point hit_win_start. Its starting point sample is traced back to GuardPre as the final leading segment start sample to avoid cutting off the leading edge.

[0162] Step 8: Accurately estimate the CFO within the hit window.

[0163] Take the original data segment with the best hit window, and... As the down-conversion frequency, the segment is shifted to baseband, and light smoothing is performed with a moving average length of approximately 2ms to reduce noise phase jitter. A complex correlation with a lag of L1 samples is then performed, and the phase increment is used to obtain the residual frequency component. Adding the relative nominal frequency to the residual frequency yields the relative nominal frequency. Final frequency offset estimation .

[0164] Step 9: Result encapsulation and exception return.

[0165] If the detection is successful: Output FOUND status. Preceding start point start_idx, Hit window start point, and two quality metrics ( / ).

[0166] If the consecutive hit condition is not met after the traversal is completed: output NOT_FOUND and set each result to NaN / empty.

[0167] Step 10: Boundary and Robustness Handling.

[0168] When the noise loop length is insufficient, it automatically degenerates into adjacent frequencies of the current window as noise; if the window length is not greater than the hysteresis L1, it automatically degenerates into a differential estimate of L1=1; the number of micro-frequency points in the fine sweep needs to be automatically corrected to an odd number to ensure that the center frequency is included in the grid.

[0169] In one specific embodiment, the simulation conditions and simulation results may be as follows.

[0170] The waveform is a 16-tone CLEW. The sampling rate Fs = 12k. Each frame is 13.33ms long. The environment is Gaussian white noise with no frequency offset. For different time-domain SNRs, a comparative test is conducted on Doppler frequency offset estimation, time-domain signal detection success rate, and false alarm probability using both traditional single-frequency detection and the two-step detection method presented in this paper. The relevant parameters of the algorithm use the reference values ​​from step 1. 10,000 Monte Carlo simulations are performed at each SNR, with each simulation consisting of 100 frames. Each frame of signal is affected by a randomly generated Doppler frequency offset between -150Hz and 150Hz.

[0171] Figure 3 This is a time-domain waveform diagram of the generated preamble real signal provided in an embodiment of the present invention.

[0172] Figure 4 This is a comparison chart of detection probability results provided in an embodiment of the present invention. (Refer to...) Figure 4 Under the same detection probability, the embodiments of the present invention achieve a detection gain of approximately 3 dB relative to the baseline.

[0173] Figure 5 This is a comparison chart of false alarm probability results provided in an embodiment of the present invention. (Refer to...) Figure 5 It can be seen that, under the same false alarm probability, the embodiment of the present invention obtains a gain of approximately 2~4dB relative to the baseline.

[0174] Figure 6 This is a comparison chart of the frequency offset estimation accuracy (RMSE, Root Mean Square Error) provided in the embodiments of the present invention. (Refer to...) Figure 6 It can be seen that, under the same frequency offset estimation accuracy, the embodiment of the present invention obtains a gain of approximately 6 dB relative to the baseline.

[0175] In summary, the embodiments of the present invention have the following technical advantages:

[0176] (1) Robust capture under wide frequency offset conditions.

[0177] In the entire real signal data segment, the nominal subcarrier frequency High-confidence time-domain detection is performed using the 605Hz Doppler reference tone from CLEW, requiring coverage of frequency offsets within ±100Hz and accurate determination of the hit window and the start point of the preamble. The start point of the preamble can then be used as the starting point for subsequent time-domain fine synchronization, allowing for more precise time-domain fine synchronization within a smaller time-domain range, rather than continuously performing time-domain fine synchronization across the entire data segment.

[0178] (2) Adaptive decision with low false alarm rate (CFAR, Constant False Alarm Rate Detection).

[0179] To address the issue of false alarms caused by fixed thresholds and single energy criteria under non-stationary noise or narrowband interference, the threshold should be adaptable to environmental changes and effectively suppress false alarm triggering.

[0180] (3) Fast estimation with low complexity.

[0181] The detection and frequency offset estimation (CFO, Carrier Frequency Offset) can be completed without performing large-point FFT, significantly reducing the computational load and online latency, making it easy to run in real time on DSP (Digital Signal Processor) / FPGA (Field-Programmable Gate Array).

[0182] (4) Quantifiable quality metric output.

[0183] Along with the detection results, it outputs quality metrics (dB values ​​of target / noise and target / adjacent frequencies) that can be used for subsequent processing, and returns the optimal hit window position and frequency peak.

[0184] The present invention provides a device for time-domain detection and Doppler frequency offset estimation of data link signals. The device described below and the method described above can be referred to in correspondence.

[0185] Figure 7 This is a schematic diagram of a time-domain detection and Doppler frequency offset estimation device for a data link signal provided in an embodiment of the present invention. (Refer to...) Figure 7 This invention provides a time-domain detection and Doppler frequency offset estimation device for data link signals, which may specifically include the following modules:

[0186] The coarse and fine scan module 710 is used to perform a sliding window detection on the entire segment of real signal data. For each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integrated power. A fine scan is performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integrated power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window, and the integrated power at the second frequency point is taken as the target integrated power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range.

[0187] The adjacent frequency reference power determination module 720 is used to determine the current adjacent frequency reference power based on the integrated power at the adjacent frequency point of the second frequency point;

[0188] The hit determination module 730 is used to determine whether the window has been hit based on the target integrated power and the current adjacent frequency reference power;

[0189] The frequency offset fine estimation module 740 is used to determine the best hit window from multiple hit windows, and perform frequency offset fine estimation within the best hit window to obtain the final frequency offset.

[0190] This invention, through a sliding window detection process on the entire real signal data segment, determines the target frequency range based on the nominal frequency and the maximum Doppler frequency shift range. For each window, a coarse scan is performed within the target frequency range to determine the first frequency point with the maximum integrated power. A fine scan is then performed, centered on the frequency corresponding to the first frequency point, to determine the second frequency point with the maximum integrated power. This achieves a two-stage search of coarse and fine scans. By replacing a large-point FFT with a time-domain DFT integration at a limited frequency point, and considering the maximum Doppler frequency shift range, it can cover a wide frequency offset and achieve high-resolution micro-scanning near the peak. The rough time-domain synchronization point can then serve as the starting point for subsequent time-domain fine synchronization, thus enabling more accurate time-domain fine synchronization within a smaller time-domain range, without needing to perform a full scan of the entire data segment. By continuously performing precise time-domain synchronization, robust acquisition under wide frequency offset conditions is achieved. By using the frequency corresponding to the second frequency point as the target peak frequency of the window and the integral power at the second frequency point as the target integral power of the window, the current adjacent frequency reference power is determined based on the integral power at the adjacent frequency point of the second frequency point. The window hit is determined based on the target integral power and the current adjacent frequency reference power. The optimal hit window is determined from multiple hit windows, and the final frequency offset is obtained by performing precise frequency offset estimation within the optimal hit window. Thus, time-domain detection and precise frequency offset estimation can be completed without performing large-point FFT, achieving fast frequency offset estimation with low complexity, reducing computational load and online latency.

[0191] Based on any of the above embodiments, the hit determination module includes:

[0192] The noise reference acquisition submodule is used to acquire the current noise reference.

[0193] The target / noise ratio calculation submodule is used to calculate the target / noise ratio based on the target integrated power and the current noise reference.

[0194] The target / adjacent-channel power ratio submodule is used to calculate the target / adjacent-channel power ratio based on the target integrated power and the current adjacent-channel reference power.

[0195] The dual-hit decision submodule is used to determine the window that simultaneously meets the first hit decision condition and the second hit decision condition as the hit window; the first hit decision condition is that the target / noise ratio is greater than or equal to a first set threshold, and the second hit decision condition is that the target / adjacent channel power ratio is greater than or equal to a second set threshold.

[0196] Based on any of the above embodiments, the noise reference acquisition submodule includes:

[0197] A noise ring queue acquisition unit is used to acquire the currently maintained noise ring queue; the noise ring queue is used to store historical adjacent frequency reference power.

[0198] The first noise reference determination unit is used to take the current adjacent frequency reference power of the window as the current noise reference if the length of the noise loop queue is less than a preset length threshold.

[0199] The second noise reference determination unit is used to take the median of the noise ring queue as the current noise reference if the length of the noise ring queue is greater than or equal to a preset length threshold.

[0200] Based on any of the above embodiments, the frequency offset fine estimation module includes:

[0201] The window hit determination submodule is used to record the information of the window into the continuous hit sequence and increment the number of continuous hits if the window is determined to be a hit window.

[0202] The missing window determination submodule is used to clear the information in the consecutive hit sequence and reset the consecutive hit count to zero if the window is determined to be a missing window.

[0203] The optimal hit window selection submodule is used to select the hit window with the largest target / noise ratio from multiple hit windows recorded in the consecutive hit sequence when the number of consecutive hits reaches a preset number.

[0204] Based on any of the above embodiments, the frequency offset fine estimation module includes:

[0205] The downconversion submodule is used to move signal data segments to the baseband within the optimal hit window, using the target peak frequency of the optimal hit window as the downconversion frequency.

[0206] The moving average smoothing submodule is used to perform short-term mean smoothing with a preset moving average length, perform complex correlation with a preset number of L1 samples, and estimate the residual frequency based on the phase increment.

[0207] The final frequency offset determination submodule is used to determine the final frequency offset based on the residual frequency, the target peak frequency of the optimal hit window, and the nominal frequency.

[0208] Based on any of the above embodiments, after performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset, the method further includes:

[0209] The first output module is used to output the detection status, the final frequency offset, the preamble start point, the sliding window start point of the optimal hit window, the target peak frequency of the optimal hit window, the target / noise ratio and the target / adjacent channel power ratio of the optimal hit window if the signal detection is successful; wherein, the sliding window start point is the starting sampling point position of the optimal hit window in the entire real signal data, and the preamble start point is obtained by backtracking backward based on the sliding window start point;

[0210] The second output module is used to return a "not found" state if a preset number of windows are not hit consecutively at the end of the window traversal.

[0211] Figure 8 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 8As shown, the electronic device may include: a processor 810, a communications interface 820, a memory 830, and a communications bus 840, wherein the processor 810, the communications interface 820, and the memory 830 communicate with each other through the communications bus 840. The processor 810 can call logic instructions in the memory 830 to execute a time-domain detection and Doppler frequency offset estimation method for a data link signal. This method includes: during sliding window detection over a whole segment of real signal data, for each window, performing a coarse scan in the target frequency range to determine the first frequency point with the largest integrated power, performing a fine scan centered on the frequency corresponding to the first frequency point to determine the second frequency point with the largest integrated power, and using the frequency corresponding to the second frequency point as the target peak frequency of the window, and using the integrated power at the second frequency point as the target integrated power of the window; the target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range; based on the integrated power at the adjacent frequency point of the second frequency point, determining the current adjacent frequency reference power; based on the target integrated power and the current adjacent frequency reference power, determining whether the window is hit; determining the optimal hit window from multiple hit windows, and performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset.

[0212] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0213] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a time-domain detection and Doppler frequency offset estimation method for a data link signal provided by the above methods. The method includes: during the sliding window detection process on the entire real signal data, for each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integrated power, and a fine scan is performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integrated power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window, and the integrated power at the second frequency point is taken as the target integrated power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range. Based on the integrated power at the adjacent frequency point of the second frequency point, the current adjacent frequency reference power is determined. Based on the target integrated power and the current adjacent frequency reference power, it is determined whether the window is hit. The best hit window is determined from multiple hit windows, and the frequency offset is finely estimated within the best hit window to obtain the final frequency offset.

[0214] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a time-domain detection and Doppler frequency offset estimation method for data link signals provided by the methods described above. The method includes: during the sliding window detection process on the entire real signal data, for each window, performing a coarse scan in the target frequency range to determine a first frequency point with the largest integrated power, performing a fine scan with the frequency corresponding to the first frequency point as the center to determine a second frequency point with the largest integrated power, and taking the frequency corresponding to the second frequency point as the target peak frequency of the window, and taking the integrated power at the second frequency point as the target integrated power of the window; the target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range; determining the current adjacent frequency reference power based on the integrated power at the adjacent frequency point of the second frequency point; determining whether the window is hit based on the target integrated power and the current adjacent frequency reference power; determining the best hit window from multiple hit windows, and performing a fine frequency offset estimation within the best hit window to obtain the final frequency offset.

[0215] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0216] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0217] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for time-domain detection and Doppler frequency offset estimation of data link signals, characterized in that, include: During the sliding window detection process on the entire real signal data, for each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integral power, and a fine scan is performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integral power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window, and the integral power at the second frequency point is taken as the target integral power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range; Based on the integrated power at the adjacent frequency point of the second frequency point, determine the current adjacent frequency reference power; Based on the target integrated power and the current adjacent frequency reference power, it is determined whether the window has been hit; The optimal hit window is determined from multiple hit windows, and a fine frequency offset estimation is performed within the optimal hit window to obtain the final frequency offset; The step of determining whether the window is hit based on the target integrated power and the current adjacent frequency reference power includes: Obtain the current noise reference; Calculate the target / noise ratio based on the target integrated power and the current noise reference; Calculate the target / adjacent channel power ratio based on the target integrated power and the current adjacent channel reference power; A window that simultaneously satisfies the first hit decision condition and the second hit decision condition is determined as a hit window; the first hit decision condition is that the target / noise ratio is greater than or equal to a first set threshold, and the second hit decision condition is that the target / adjacent channel power ratio is greater than or equal to a second set threshold; The step of determining the optimal hit window from multiple hit windows includes: If the window is determined to be a hit window, the information of the window is recorded in the consecutive hit sequence, and the consecutive hit count is incremented by one; If the window is determined to be a missed window, the information in the consecutive hit sequence is cleared and the consecutive hit count is reset to zero. When the number of consecutive hits reaches a preset number, the hit window with the largest target / noise ratio is selected from multiple hit windows recorded in the consecutive hit sequence as the best hit window; The step of performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset includes: Within the optimal hit window, the target peak frequency of the optimal hit window is used as the down-conversion frequency to move the signal data segment to the baseband. Short-time mean smoothing is performed with a preset moving average length, complex correlation is performed with a preset number of L1 samples, and the residual frequency is estimated based on the phase increment. The final frequency offset is determined based on the residual frequency, the target peak frequency of the optimal hit window, and the nominal frequency.

2. The time-domain detection and Doppler frequency offset estimation method for data link signals according to claim 1, characterized in that, The step of obtaining the current noise reference includes: Obtain the currently maintained noise ring queue; the noise ring queue is used to store historical adjacent frequency reference power; If the length of the noise loop queue is less than a preset length threshold, then the current adjacent frequency reference power of the window is used as the current noise reference. If the length of the noise ring queue is greater than or equal to a preset length threshold, then the median of the noise ring queue is used as the current noise benchmark.

3. The time-domain detection and Doppler frequency offset estimation method for data link signals according to claim 1, characterized in that, After performing fine frequency offset estimation within the optimal hit window to obtain the final frequency offset, the process further includes: If signal detection is successful, the following information is output: detection status, final frequency offset, preamble start point, sliding window start point of the optimal hit window, target peak frequency of the optimal hit window, target / noise ratio and target / adjacent channel power ratio of the optimal hit window; wherein, the sliding window start point is the starting sampling point position of the optimal hit window in the entire real signal data, and the preamble start point is obtained by backtracking backward based on the sliding window start point; If the preset number of windows are not hit consecutively by the end of the window traversal, the system returns to the "not found" state.

4. A device for time-domain detection and Doppler frequency offset estimation of a data link signal, characterized in that, include: The coarse and fine scan modules are used to perform sliding window detection on the entire real signal data. For each window, a coarse scan is performed in the target frequency range to determine the first frequency point with the largest integral power. A fine scan is performed with the frequency corresponding to the first frequency point as the center to determine the second frequency point with the largest integral power. The frequency corresponding to the second frequency point is taken as the target peak frequency of the window. The integral power at the second frequency point is taken as the target integral power of the window. The target frequency range is determined based on the nominal frequency and the maximum Doppler frequency shift range; The adjacent frequency reference power determination module is used to determine the current adjacent frequency reference power based on the integrated power at the adjacent frequency point of the second frequency point; The hit determination module is used to determine whether the window has been hit based on the target integrated power and the current adjacent frequency reference power; The frequency offset fine estimation module is used to determine the best hit window from multiple hit windows, and perform frequency offset fine estimation within the best hit window to obtain the final frequency offset; The hit determination module includes: The noise reference acquisition submodule is used to acquire the current noise reference. The target / noise ratio calculation submodule is used to calculate the target / noise ratio based on the target integrated power and the current noise reference. The target / adjacent-channel power ratio submodule is used to calculate the target / adjacent-channel power ratio based on the target integrated power and the current adjacent-channel reference power. The dual-hit decision submodule is used to determine the window that simultaneously meets the first hit decision condition and the second hit decision condition as the hit window; the first hit decision condition is that the target / noise ratio is greater than or equal to a first set threshold, and the second hit decision condition is that the target / adjacent channel power ratio is greater than or equal to a second set threshold; The frequency offset fine estimation module includes: The window hit determination submodule is used to record the information of the window into the continuous hit sequence and increment the number of continuous hits if the window is determined to be a hit window. The missing window determination submodule is used to clear the information in the consecutive hit sequence and reset the consecutive hit count to zero if the window is determined to be a missing window. The optimal hit window selection submodule is used to select the hit window with the largest target / noise ratio from multiple hit windows recorded in the consecutive hit sequence when the number of consecutive hits reaches a preset number. The frequency offset fine estimation module includes: The downconversion submodule is used to move signal data segments to the baseband within the optimal hit window, using the target peak frequency of the optimal hit window as the downconversion frequency. The moving average smoothing submodule is used to perform short-term mean smoothing with a preset moving average length, perform complex correlation with a preset number of L1 samples, and estimate the residual frequency based on the phase increment. The final frequency offset determination submodule is used to determine the final frequency offset based on the residual frequency, the target peak frequency of the optimal hit window, and the nominal frequency.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements a time-domain detection and Doppler frequency offset estimation method for a data link signal as described in any one of claims 1 to 3.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a time-domain detection and Doppler frequency offset estimation method for a data link signal as described in any one of claims 1 to 3.

7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements a time-domain detection and Doppler frequency offset estimation method for a data link signal as described in any one of claims 1 to 3.

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