Detection device, detection method, electronic device, computer-readable storage medium, and computer program product

Abstract

This disclosure provides a detection device, detection method, electronic device, computer-readable storage medium, and computer program product. The detection device includes: a reference value generation module for generating a reference value based on a detected signal; a first autocorrelation module for performing autocorrelation calculation and moving average processing on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration; a second autocorrelation module for performing autocorrelation calculation and moving average processing on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration; a difference module for performing difference processing on the first value and at least one second value to obtain at least one difference value; and a detection module for comparing the reference value and at least one difference value to obtain a detection result.

Description

Technical Field

[0001] This disclosure relates to the field of electronic information technology, and in particular to a detection device, detection method, electronic device, computer-readable storage medium, and computer program product. Background Technology

[0002] WiFi is a wireless local area network communication technology based on the IEEE 802.11 standard. WiFi synchronization technology is one of the core algorithms of its physical layer, used to reliably capture data packets in complex wireless environments, especially in multi-antenna scenarios. In practical scenarios, routers are typically multi-antenna (e.g., two, three, four antennas, etc.). Correlation detection methods refer to calculating the start position by performing cross-correlation and autocorrelation on short training sequences in the preamble of WiFi data packets; essentially, they are all based on the correlation between symbols.

[0003] In related technologies, cross-correlation detection for multi-antenna routers introduces coherent interference, causing destructive interference and leading to direct packet loss. In contrast, autocorrelation detection schemes are robust to multi-antenna scenarios; however, due to the inherently strong, even perfect, self-similarity of single-tone and narrowband signals, autocorrelation detectors can produce false alarms. Therefore, resolving the false alarm problem caused by autocorrelation detection due to single-tone and narrowband interference is crucial. Summary of the Invention

[0004] This disclosure provides a detection device, a detection method, an electronic device, a computer-readable storage medium, and a computer program product.

[0005] In a first aspect, embodiments of this disclosure provide a detection device, including: A reference value generation module is used to receive the detected signal and generate a reference value based on the detected signal, wherein the reference value indicates a reference energy value; The first autocorrelation module is used to perform autocorrelation calculation and moving average processing based on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of the short training sequence; The second autocorrelation module is used to perform autocorrelation calculation and moving average processing based on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration being not an integer multiple of the period of the short training sequence; A difference module is used to perform difference processing on the first value and at least one of the second values ​​to obtain at least one difference value; A detection module is used to compare the reference value with at least one of the difference values ​​to obtain a detection result.

[0006] In some embodiments, the detection module is further configured to determine that the short training sequence has been detected when the difference value is greater than the reference value; or, determine that the short training sequence has not been detected when the difference value is less than the reference value.

[0007] In some embodiments, the detection device further includes: The sampling module is used to perform analog-to-digital conversion and downsampling on the initial detection signal to obtain the detected signal.

[0008] In some embodiments, the first autocorrelation module includes: The first delay unit is used to delay the detected signal by multiple different first delay durations to obtain multiple basic delay signals; The first autocorrelation unit is used to perform autocorrelation calculations on the detected signal and each of the basic delay signals to obtain multiple first autocorrelation signals; The first addition unit is used to coherently superimpose multiple first autocorrelation signals to obtain a first superimposed signal; The first moving average unit is used to perform moving average processing on the first superimposed signal with a window equal to the period of the short training sequence to obtain the first average signal. The first complex number calculation unit is used to perform complex number calculations on the first average signal to obtain the first value.

[0009] In some embodiments, the second autocorrelation module includes at least one correlation submodule, each of which is used to generate a second value according to a preset second delay duration; The values ​​of the second delay duration are different in different related sub-modules.

[0010] In some embodiments, each of the related submodules includes: The second delay unit is used to delay the detected signal by multiple different second delay durations to obtain multiple interference delay signals; wherein the delay duration of two adjacent interference delay signals differs from the period of the short training sequence; The second autocorrelation unit is used to perform autocorrelation calculations on the detected signal and each of the interference delay signals to obtain multiple second autocorrelation signals; The second addition unit is used to coherently superimpose multiple second autocorrelation signals to obtain a second superimposed signal; The second moving average unit is used to perform moving average processing on the second superimposed signal with a window of the period of the short training sequence to obtain the second average signal; The second complex number calculation unit is used to perform complex number calculations on the second average signal to obtain the second value.

[0011] In some embodiments, the reference value generation module includes: A reference complex number calculation unit is used to perform complex number calculations on the detected signal to obtain an intermediate value; A reference moving average unit is used to perform a moving average processing on the intermediate value with a window of the period of the short training sequence to obtain the average value; A reference delay unit is used to delay the average value by multiple different first delay durations to obtain multiple delay values; A reference autocorrelation unit is used to perform autocorrelation calculations on the average value and each of the delay values ​​to obtain multiple autocorrelation values; The reference addition unit is used to perform addition calculations and numerical transformations on multiple autocorrelation values ​​to obtain the reference value.

[0012] In some embodiments, the detection module includes a logic processing unit and a plurality of comparison and detection units, wherein the number of related sub-modules is equal to the number of comparison and detection units; wherein: Each of the comparison and detection units is used to compare the reference value and the corresponding difference value, and when the difference value is greater than the reference value, to perform plateau peak detection processing on the difference between the difference value and the reference value to obtain a detection value; The logic processing unit is configured to determine that the short training sequence has been detected when any of the detection values ​​is in a first level state; or, when all the detection values ​​are in a second level state, determine that the short training sequence has not been detected.

[0013] In some embodiments, the number of the basic delay signals is equal to the number of the delay values.

[0014] Secondly, embodiments of this disclosure provide a detection method, including: Receive the detected signal and generate a reference value based on the detected signal, the reference value indicating a reference energy value; A first value is obtained by performing autocorrelation calculation and moving average processing on the detected signal and at least one basic delay signal; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of the short training sequence; Autocorrelation calculation and moving average processing are performed on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration being not an integer multiple of the period of the short training sequence; The first value and at least one of the second values ​​are differentially processed to obtain at least one difference value; The reference value and at least one of the difference values ​​are compared to obtain the detection result.

[0015] In some embodiments, comparing the reference value with at least one of the difference values ​​to obtain the detection result includes: When the difference value is greater than the reference value, it is determined that the short training sequence has been detected; or, when the difference value is less than the reference value, it is determined that the short training sequence has not been detected.

[0016] In some embodiments, the method further includes: The initial detection signal is subjected to analog-to-digital conversion and downsampling to obtain the detected signal.

[0017] In some embodiments, the first value is obtained by performing autocorrelation calculation and moving average processing based on the detected signal and at least one of the underlying delay signals, including: The detected signal is delayed by multiple different first delay durations to obtain multiple basic delay signals; Autocorrelation calculations are performed on the detected signal and each of the underlying delay signals to obtain multiple first autocorrelation signals; The first autocorrelation signals are coherently superimposed to obtain the first superimposed signal; The first superimposed signal is processed by a moving average with a window equal to the period of the short training sequence to obtain the first average signal; The first value is obtained by performing complex number calculations on the first average signal.

[0018] In some embodiments, the method further includes: The relevant submodules generate a second value based on the preset second delay duration; The values ​​of the second delay duration are different in different related sub-modules.

[0019] In some embodiments, the second value is obtained by performing autocorrelation calculation and moving average processing based on the detected signal and at least one of the interference delay signals, including: The detected signal is delayed by multiple different second delay durations to obtain multiple interference delay signals; wherein the delay duration of two adjacent interference delay signals differs from the period of the short training sequence. Autocorrelation calculations are performed on the detected signal and each of the interference delay signals to obtain multiple second autocorrelation signals; The second autocorrelation signals are coherently superimposed to obtain the second superimposed signal; The second superimposed signal is processed by a moving average with a window equal to the period of the short training sequence to obtain the second average signal; The second average signal is subjected to complex number calculations to obtain the second value.

[0020] In some embodiments, generating the reference value based on the detected signal includes: Perform complex number calculations on the detected signal to obtain an intermediate value; The intermediate value is processed by a moving average with a window equal to the period of the short training sequence to obtain the average value; By delaying the average value by multiple different first delay durations, multiple delay values ​​are obtained; Autocorrelation is calculated on the average value and each of the delay values ​​to obtain multiple autocorrelation values; The reference value is obtained by performing addition calculations and numerical transformations on multiple autocorrelation values.

[0021] In some embodiments, comparing the reference value with at least one of the difference values ​​to obtain the detection result includes: The reference value and the corresponding difference value are compared, and if the difference value is greater than the reference value, a plateau peak detection process is performed on the difference between the difference value and the reference value to obtain a detection value. When any of the detected values ​​is at the first level, it is determined that the short training sequence has been detected; or, when all the detected values ​​are at the second level, it is determined that the short training sequence has not been detected.

[0022] In some embodiments, the number of the basic delay signals is equal to the number of the delay values.

[0023] Thirdly, embodiments of this disclosure provide an electronic device, including a memory and a processor, wherein: The memory is used to store computer programs that can run on the processor; The processor is configured to execute the method as described in any one of the second aspects when running the computer program.

[0024] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing a computer program that, when executed by at least one processor, implements the method as described in any one of the second aspects.

[0025] Fifthly, embodiments of this disclosure provide a computer program product comprising a computer program that, when executed by at least one processor, implements the method as described in any one of the second aspects.

[0026] This disclosure provides a detection device, detection method, electronic device, computer-readable storage medium, and computer program product. The detection device includes: a reference value generation module for receiving a detected signal and generating a reference value based on the detected signal, the reference value indicating a reference energy value; a first autocorrelation module for performing autocorrelation calculation and moving average processing on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of a short training sequence; a second autocorrelation module for performing autocorrelation calculation and moving average processing on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration not being an integer multiple of the period of a short training sequence; a difference module for performing difference processing on the first value and at least one second value to obtain at least one difference value; and a detection module for comparing the reference value and at least one difference value to obtain a detection result. In this disclosure, the second delay duration is not an integer multiple of the period of the short training sequence, but is related to the period of the interference signal. The interference signal exhibits strong autocorrelation not only at integer multiples of the period of the short training sequence but also at its own period. Conversely, the short training sequence shows almost no autocorrelation at the period of the interference signal. Therefore, the first value is a combined result of autocorrelation detection of both the short training sequence and the interference signal, while the second value is only the result of autocorrelation detection of the interference signal. Differential processing of the first value and at least one second value can remove the interference and influence of the interference signal. Furthermore, the reference value indicates a baseline energy value. By comparing the reference value with at least one differential value to obtain the detection result, the influence of the absolute signal strength can be eliminated. Thus, this detection device effectively eliminates false alarms caused by interference signals (such as single-tone signals and narrowband signals) while ensuring packet detection requirements and detection probability, effectively improving the performance of multi-antenna packet detection and effectively compensating for packet loss problems in cross-correlation detection under multi-antenna conditions. Attached Figure Description

[0027] Figure 1 A schematic diagram of the structure of a detection device provided in an embodiment of this disclosure. Figure 1 ; Figure 2 A schematic diagram of the structure of a detection device provided in an embodiment of this disclosure. Figure 2 ; Figure 3 A schematic diagram of the structure of a detection device provided in an embodiment of this disclosure. Figure 3 ; Figure 4 A schematic diagram of the frame of a detection device provided in an embodiment of this disclosure; Figure 5 A schematic flowchart of a detection method provided in an embodiment of this disclosure; Figure 6 A schematic diagram of the structure of an electronic device provided in this disclosure embodiment. Figure 1 ; Figure 7 A schematic diagram of the structure of an electronic device provided in this disclosure embodiment. Figure 2 . Detailed Implementation

[0028] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining the relevant applications and are not intended to limit the scope of this disclosure. Furthermore, it should be noted that, for ease of description, only the parts relevant to the relevant applications are shown in the accompanying drawings.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing embodiments of this disclosure only and is not intended to be limiting of this disclosure.

[0030] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0031] It should be noted that the terms "first, second, third" used in the embodiments of this disclosure are merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of this disclosure described herein can be implemented in an order other than that illustrated or described herein.

[0032] In autocorrelation detection, the traditional short training sequence (Legacy Short Training Field, L-STF) and the detection signal delayed by 16 points (i.e., 16 sampling points) are used to calculate the autocorrelation, and the coarse synchronization position is determined by the peak position of the platform.

[0033] In related technologies, autocorrelation detection and cross-correlation detection are performed simultaneously. In multi-antenna scenarios, the performance of cross-correlation detection degrades, leading to direct packet loss. Although autocorrelation detection performs well in this scenario and can compensate for the problems in cross-correlation detection, it is prone to false alarms due to interference from single-tone signals and narrowband signals. False alarms refer to the frequent reporting of detected data packets when there is no WiFi signal.

[0034] Based on this, this disclosure provides a detection device, comprising: a reference value generation module for receiving a detected signal and generating a reference value based on the detected signal, the reference value indicating a reference energy value; a first autocorrelation module for performing autocorrelation calculation and moving average processing on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of a short training sequence; a second autocorrelation module for performing autocorrelation calculation and moving average processing on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration not being an integer multiple of the period of a short training sequence; a difference module for performing difference processing on the first value and at least one second value to obtain at least one difference value; and a detection module for comparing the reference value and at least one difference value to obtain a detection result. In this disclosure, the second delay duration is not an integer multiple of the period of the short training sequence, but is related to the period of the interference signal. The interference signal exhibits strong autocorrelation not only at integer multiples of the period of the short training sequence but also at its own period. Conversely, the short training sequence shows almost no autocorrelation at the period of the interference signal. Therefore, the first value is a combined result of autocorrelation detection of both the short training sequence and the interference signal, while the second value is only the result of autocorrelation detection of the interference signal. Differential processing of the first value and at least one second value can remove the interference and influence of the interference signal. Furthermore, the reference value indicates a baseline energy value. By comparing the reference value with at least one differential value to obtain the detection result, the influence of the absolute signal strength can be eliminated. Thus, this detection device effectively eliminates false alarms caused by interference signals (such as single-tone signals and narrowband signals) while ensuring packet detection requirements and detection probability, effectively improving the performance of multi-antenna packet detection and effectively compensating for packet loss problems in cross-correlation detection under multi-antenna conditions.

[0035] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0036] In one embodiment of this disclosure, see Figure 1 It shows a schematic diagram of the structure of a detection device provided in an embodiment of this disclosure. Figure 1.like Figure 1 As shown, the detection device 10 may include: The reference value generation module 11 is used to receive the detected signal and generate a reference value based on the detected signal. The reference value indicates the reference energy value. The first autocorrelation module 12 is used to perform autocorrelation calculation and moving average processing based on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of the short training sequence; The second autocorrelation module 13 is used to perform autocorrelation calculation and moving average processing based on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, and the second delay duration is not equal to an integer multiple of the period of the short training sequence; Difference module 14 is used to perform difference processing on the first value and at least one second value to obtain at least one difference value; The detection module 15 is used to compare the reference value with at least one difference value to obtain the detection result.

[0037] like Figure 1 As shown, the first autocorrelation module 12 and the second autocorrelation module 13 receive the detected signal, the differential module 14 receives a first value and at least one second value, and the detection module 15 receives a reference value and at least one differential value.

[0038] This disclosure provides a detection device 10, specifically an autocorrelation detection structure that can eliminate false alarms caused by interference from single-tone signals and narrowband signals. The autocorrelation detection structure is specifically an autocorrelation differential structure that can be applied to the Internet of Things.

[0039] Autocorrelation refers to the correlation between a signal and itself at different points in time, or the similarity between a signal and a copy of itself after a certain delay. When a signal has a periodic or repetitive pattern, the autocorrelation value after a delay of an integer multiple of the period is very high.

[0040] It should be noted that the signal being detected can be referred to as the current data signal. This disclosure does not specifically limit the type of signal being detected; exemplarily, the signal being detected is a WiFi signal, primarily targeting Orthogonal Frequency Division Multiplexing (OFDM) signals. The WiFi data packet begins with a short training sequence consisting of 10 repeating short symbols, each 0.8 microseconds (μs) long, exhibiting perfect periodicity.

[0041] Assuming the current data signal has a sampling rate of 20 MHz (M) and each sampling point has a duration of 50 nanoseconds (ns), the 16-point autocorrelation false alarm generated by a single-tone signal at a periodic multiple of 1.25 MHz is the most significant. Understandably, a single-tone signal at a periodic multiple of 1.25 MHz perfectly simulates the periodicity of the L-STF repeating every 0.8 μs, thus generating the largest and most sustained output in the 16-point autocorrelation calculation, leading to the most severe false alarms. At a sampling rate of 20 MHz, 0.8 μs corresponds exactly to 16 sampling points, which constitute a short symbol. When the sampling rate changes, the number of sampling points changes accordingly, but the period of the 0.8 μs short symbol remains unchanged.

[0042] In this embodiment, the period of the short training sequence is 0.8 μs (i.e., 800 ns). The first delay duration can be one, two, or three times the period of the short training sequence, etc., or in other words, the first delay duration can be one period of the short training sequence, two periods of the short training sequence, or three periods of the short training sequence, etc.

[0043] It should also be noted that the second delay duration is not an integer multiple of the period of the short training sequence; it is related to the period of the interference signal, which includes at least single-tone signals and narrowband signals. For the short training sequence, the autocorrelation is strong every 800ns, but for the interference signal, the autocorrelation is strong not only every 800ns but also throughout the interference signal's period. However, the short training sequence has almost no autocorrelation within the interference signal's period. Understandably, the first value is the combined result of autocorrelation detection of both the short training sequence and the interference signal, while the second value is only the result of autocorrelation detection of the interference signal. Subtracting the two yields the difference value. Utilizing the difference in autocorrelation between the short training sequence and the interference signal at different periods, the difference value can remove the interference and influence of the interference signal. The period of the interference signal can be slightly offset from the period of the short training sequence, for example, 805ns, 850ns, or 900ns, etc. There is no specific limitation; it can be set according to the actual situation.

[0044] In this embodiment, the first autocorrelation module 12 is used to calculate signal correlation, and the second autocorrelation module 13 is used to calculate the correlation between single-tone signals and narrowband signal interference. The period of the short training sequence is periodic at 16 points, meaning the first delay duration is based on a periodic 16-point interval; while the period of the interference signal is not aperiodic at 16 points, meaning the second delay duration is based on aperiodic at 16 points. When the first autocorrelation module 12 performs autocorrelation calculation, it satisfies an 800ns periodicity; when the second autocorrelation module 13 performs autocorrelation calculation, it does not satisfy an 800ns periodicity.

[0045] It should also be noted that the specific methods for performing autocorrelation calculation and moving average processing can adopt common methods in related technologies, which will not be elaborated here in this embodiment. After performing autocorrelation calculation, the first autocorrelation module 12 and the second autocorrelation module 13 perform moving average processing, which can eliminate some spikes in the results obtained after autocorrelation calculation and improve the detection accuracy.

[0046] When there are multiple second values, the difference module 14 is specifically used to perform difference processing on the first value and each second value respectively. Specifically, each second value is subtracted from the first value to obtain multiple difference values. That is, the first value is used as the "minuend" of the difference structure, and the second value is used as the "subtrahend" of the difference structure.

[0047] In this embodiment, the reference value generation module 11 is also used to receive the detected signal, but the order in which different processes are performed on the detected signal is different. For example, the reference value generation module 11 is used to perform complex number calculation and moving average processing on the detected signal to obtain an average value, and to perform autocorrelation calculation based on the average value and at least one delay value to obtain a reference value; the delay value is obtained by delaying the average value by a first delay duration.

[0048] Complex number calculation refers to taking the absolute value (abs), or modulus value. Specifically, it can be approximated by modulus (Mod Approx).

[0049] It should also be noted that the reference value is specifically a reference energy benchmark, used to measure whether the autocorrelation calculation result is abnormal. Specifically, if the detected signal is non-periodic, such as pure noise, but the signal is very strong, the absolute value of the autocorrelation calculation will also be large. The reference energy benchmark can eliminate the influence of the absolute signal strength, making the detection threshold independent of signal strength, thereby achieving constant false alarm rate detection. In other words, the reference energy benchmark ensures that the false alarm probability no longer changes with signal strength. The reference value can be determined based on the actual situation.

[0050] Here, the detection result is whether a short training sequence (or data packet header) is detected.

[0051] In some embodiments, the detection module 15 is further configured to determine that a short training sequence has been detected when the difference value is greater than a reference value; or, to determine that a short training sequence has not been detected when the difference value is less than a reference value.

[0052] Understandably, if the difference value is greater than the reference value, it means the difference value is greater than the absolute signal strength, and the detection module 15 can detect the short training sequence, indicating that a data packet has been captured. Conversely, if the difference value is less than the reference value, it means the difference value is less than the absolute signal strength, and the detection module 15 has not detected the short training sequence, indicating that the detected signal only contains noise or interference signals, and a data packet has not yet been captured. In some embodiments, such as Figure 2 As shown, the detection device 10 may further include: The sampling module 16 is used to perform analog-to-digital conversion and downsampling on the initial detection signal to obtain the detected signal.

[0053] like Figure 2 As shown, sampling module 16 receives the initial detection signal.

[0054] The initial detection signal is the data signal to be received, which is the data packet to be received. The type of the initial detection signal can be determined based on the type of communication network. For example, the initial detection signal can be a WiFi data packet used for wireless communication.

[0055] It should be noted that the continuous radio signal (i.e., the initial detection signal) is processed by the sampling module 16 and then undergoes analog-to-digital conversion (ADC) to convert it into a discrete digital signal. After conversion, downsampling is performed, i.e., the sampling rate of the digital signal is reduced; for example, the digital signal is downsampled to 20MHz, and the downsampled frequency is the sampling rate (20MHz) of the signal being detected. In essence, the initial detection signal is sampled by the ADC and downsampled to a 20MHz baseband sampling rate to obtain the signal being detected.

[0056] In this embodiment, the number of basic delay signals can be determined according to the actual situation of the application, and there is no specific limitation thereto. For example, the number of basic delay signals is multiple.

[0057] In some embodiments, such as Figure 3 As shown, the first autocorrelation module 12 may include: The first delay unit 121 is used to delay the detected signal by multiple different first delay durations to obtain multiple basic delay signals; The first autocorrelation unit 122 is used to perform autocorrelation calculations on the detected signal and each basic delay signal to obtain multiple first autocorrelation signals; The first addition unit 123 is used to coherently superimpose multiple first autocorrelation signals to obtain a first superimposed signal; The first moving average unit 124 is used to perform moving average processing on the first superimposed signal with a window of a short training sequence period to obtain the first average signal. The first complex number calculation unit 125 is used to perform complex number calculations on the first average signal to obtain the first value.

[0058] like Figure 3 As shown, the first delay unit 121 receives the detected signal, the first autocorrelation unit 122 receives the detected signal and multiple basic delay signals, the first addition unit 123 receives multiple first autocorrelation signals, the first moving average unit 124 receives the first superimposed signal, and the first complex number calculation unit 125 receives the first average signal.

[0059] It should be noted that this embodiment does not specifically limit the number of periods of the short training sequence included in each first delay duration, but the number of periods of the short training sequence included in the first delay duration corresponding to multiple basic delay signals is different. The detected signal is delayed multiple times by the first delay unit 121 to generate multiple basic delay signals corresponding to the detected signal at multiple different time points; then the first autocorrelation unit 122 performs autocorrelation calculation on the detected signal and each basic delay signal respectively. By performing multiple autocorrelation calculations on the detected signal and its own multiple basic delay signals corresponding to multiple different time points, a higher cumulative correlation gain is obtained, which can improve the data packet detection performance, effectively detect data packets, and avoid data packet loss. This embodiment does not specifically limit the number of basic delay signals. For example, the number of basic delay signals is 3. The detected signal is delayed by 3 different first delay durations by the first delay unit 121, that is, the detected signal is delayed by 1 period of short training sequence (i.e., 800ns), 2 periods of short training sequence (i.e., 1600ns), and 3 periods of short training sequence (i.e., 2400ns), respectively, to obtain 3 basic delay signals. The first delay durations corresponding to the 3 basic delay signals include 1, 2, and 3 periods of short training sequence, respectively.

[0060] It should also be noted that the first autocorrelation signal, the first superposition signal, and the first average signal are all complex signals. Complex signals simultaneously represent both numerical value and phase, and the first value obtained after performing complex calculations is a numerical value.

[0061] In some embodiments, the window for performing the moving average processing on the first superimposed signal can be an integer multiple of the period of the short training sequence. That is, the window for performing the moving average processing on the first superimposed signal can be the period of the short training sequence itself, or it can be twice or three times the period of the short training sequence, etc., which can be determined according to the actual situation.

[0062] It should be noted that the moving average processing may include truncation processing, which can shorten the bit width. This embodiment does not specifically limit the specific position and number of bits for truncation processing. For example, the lower bits are truncated, specifically the lower 4 bits (i.e., Trunc 4 bits). This can reduce the amount of subsequent calculations, improve the calculation speed, and reduce power consumption.

[0063] In some embodiments, such as Figure 3 As shown, the second autocorrelation module 13 may include at least one correlation submodule 131, each correlation submodule 131 being used to generate a second value according to a preset second delay duration; The values ​​of the second delay duration are different in different related submodules 131.

[0064] It should be noted that the interference delay signal is obtained by delaying the detected signal by a second delay time. Each correlation submodule 131 is used to receive the detected signal, perform autocorrelation calculation and moving average processing on the detected signal and at least one interference delay signal to obtain a second value. Because the corresponding second delay time values ​​are different in different correlation submodules 131, the obtained interference delay signals are different, and thus the second value generated by each correlation submodule 131 is also different.

[0065] This embodiment does not specifically limit the number of correlation sub-modules 131 in the second autocorrelation module 13. For example, the second autocorrelation module 13 includes two correlation sub-modules 131. The implementation of the autocorrelation difference structure calculation module (i.e., the detection device 10) is not limited to two sets of difference structures (i.e., two correlation sub-modules 131). The number of difference groups can be reduced or increased according to the actual application to obtain suitable detection performance. In some embodiments, such as... Figure 3 As shown, each relevant submodule 131 may include: The second delay unit 1311 is used to delay the detected signal by multiple different second delay durations to obtain multiple interference delay signals; the delay durations of two adjacent interference delay signals differ by a short period of the training sequence. The second autocorrelation unit 1312 is used to perform autocorrelation calculations on the detected signal and each interference delay signal to obtain multiple second autocorrelation signals. The second addition unit 1313 is used to coherently superimpose multiple second autocorrelation signals to obtain a second superimposed signal; The second moving average unit 1314 is used to perform moving average processing on the second superimposed signal with a window of a short training sequence period to obtain the second average signal. The second complex number calculation unit 1315 is used to perform complex number calculations on the second average signal to obtain the second value.

[0066] like Figure 3 As shown, the second delay unit 1311 receives the detected signal, the second autocorrelation unit 1312 receives the detected signal and multiple interference delay signals, the second addition unit 1313 receives multiple second autocorrelation signals, the second moving average unit 1314 receives the second superimposed signal, and the second complex number calculation unit 1315 receives the second average signal.

[0067] The values ​​of the second delay durations are different in different correlation submodules 131; for each correlation submodule 131, the detected signal is delayed by multiple different second delay durations to obtain multiple interference delay signals. Understandably, the multiple interference delay signals obtained by multiple correlation submodules 131 are all different.

[0068] It should be noted that the delay duration of the first interference delay signal and the detected signal in each correlation submodule 131 differs by a preset delay duration, and the preset delay durations for multiple correlation submodules 131 are different. In each correlation submodule 131, the first interference delay signal is obtained by delaying the detected signal by the preset delay duration, where the preset delay duration is related to the period of the interference signal. In the case where the second autocorrelation module 13 includes two correlation submodules 131, the preset delay duration of one correlation submodule 131 is denoted by K1, and the preset delay duration of the other correlation submodule 131 is denoted by K2. The specific values ​​of K1 and K2 are different and can be obtained through simulation. The difference between K1 and K2 determines the different interference correlations of single-tone signals and narrowband signals. Through K1 and K2, the autocorrelation of the short training sequence is disrupted, making the period of the interference signal not an integer multiple of 800ns.

[0069] It should also be noted that the detected signal is delayed multiple times by the second delay unit 1311 to generate multiple interference delay signals corresponding to the detected signal at multiple different time points; then, the second autocorrelation unit 1312 performs autocorrelation calculation on the detected signal and each interference delay signal respectively. By performing multiple autocorrelations between the detected signal and its own multiple interference delay signals corresponding to multiple different time points, a higher correlation cumulative gain is obtained, which can improve the data packet detection performance, effectively detect data packets, and avoid data packet loss. This embodiment does not specifically limit the number of interference delay signals. For example, the number of interference delay signals is 3. The detected signal is delayed by 3 different second delay durations by the second delay unit 1311. In one correlation submodule 131, the detected signal is delayed by K1ns, (K1+800)ns, and (K1+1600)ns respectively to obtain 3 interference delay signals; in another correlation submodule 131, the detected signal is delayed by K2ns, (K2+800)ns, and (K2+1600)ns respectively to obtain 3 interference delay signals. In one correlation submodule 131, K1ns and (K1+800)ns differ by 800ns, and (K1+800)ns and (K1+1600)ns differ by 800ns. The delay durations of two adjacent interference delay signals differ by a period shorter than the training sequence. Furthermore, if each correlation submodule 131 corresponds to a larger number of interference delay signals, such as four, these can be obtained by delaying the detected signal by (K1+2400)ns or (K2+2400)ns.

[0070] In this embodiment, the number of basic delay signals corresponding to the first autocorrelation module 12 and the number of interference delay signals corresponding to the second autocorrelation module 13 can be set according to actual conditions, and the number of interference delay signals corresponding to each correlation submodule 131 in the second autocorrelation module 13 can also be set according to actual conditions, without any specific limitation. If packet detection requirements are strict, the number of basic delay signals and / or the number of correlation submodules 131 and / or the number of interference delay signals corresponding to each correlation submodule 131 can be increased to improve detection accuracy.

[0071] Here, the second autocorrelation signal, the second superposition signal, and the second average signal are all complex signals, and the second value is a numerical value.

[0072] In some embodiments, the window for performing the moving average processing on the second superimposed signal can be an integer multiple of the period of the short training sequence. That is, the window for performing the moving average processing on the second superimposed signal can be the period of the short training sequence itself, or it can be twice or three times the period of the short training sequence, etc., which can be determined according to the actual situation.

[0073] In some embodiments, such as Figure 3 As shown, the reference value generation module 11 may include: The reference complex number calculation unit 111 is used to perform complex number calculations on the detected signal to obtain an intermediate value; The reference moving average unit 112 is used to perform a moving average processing on the intermediate value with a window of short training sequence period to obtain the average value; Reference delay unit 113 is used to delay the average value by multiple different first delay durations to obtain multiple delay values; Reference autocorrelation unit 114 is used to perform autocorrelation calculations on the average value and each delay value to obtain multiple autocorrelation values; Reference addition unit 115 is used to perform addition calculations and numerical transformations on multiple autocorrelation values ​​to obtain reference values.

[0074] like Figure 3 As shown, the reference complex number calculation unit 111 receives the detected signal, the reference moving average unit 112 receives the intermediate value, the reference delay unit 113 receives the average value, the reference autocorrelation unit 114 receives the average value and multiple delay values, and the reference addition unit 115 receives multiple autocorrelation values.

[0075] It should be noted that the reference adder unit 115 first adds multiple autocorrelation values, and then performs a numerical transformation on the added value, that is, multiplies the added value by a scaling factor (which can be represented by pwrWeight). The scaling factor is a multiplicative constant; multiplying it by a variable, function, or signal will scale it in the corresponding dimension. The specific value of the scaling factor can be determined according to the actual situation and can be obtained through simulation. The sensitivity of the reference value can be adjusted through the scaling factor. For example, the scaling factor is represented by an unsigned 4-bit value (which can be represented by unsigned 4-bit).

[0076] In some embodiments, the window for applying a moving average to the intermediate value can be an integer multiple of the period of the short training sequence. That is, the window for applying a moving average to the intermediate value can be the period of the short training sequence itself, or it can be twice or three times the period of the short training sequence, etc., which can be determined according to the actual situation.

[0077] In some embodiments, the reference addition unit 115 is further configured to perform truncation processing on the numerical values ​​obtained after adding and transforming multiple autocorrelation values ​​to obtain a reference value.

[0078] This embodiment does not specifically limit the location and number of bits for truncation. For example, the lower-order bits are truncated, specifically the lower 4 bits. This reduces the amount of subsequent calculations, increases calculation speed, and reduces power consumption. Furthermore, multiplying by a scaling factor before truncation ensures data accuracy.

[0079] It should be noted that by delaying the average value by multiple different first delay durations using the reference delay unit 113, multiple delay values ​​corresponding to the average value at multiple different time points are obtained. This embodiment does not specifically limit the number of delay values.

[0080] In some embodiments, the number of basic delay signals is equal to the number of delay values.

[0081] For example, when there are 3 basic delay signals, there are also 3 delay values. The average value is delayed by 3 different first delay durations by the reference delay unit 113, that is, the average value is delayed by 1 period of short training sequence, 2 periods of short training sequence, and 3 periods of short training sequence, respectively, to obtain 3 delay values. The first delay durations corresponding to these 3 delay values ​​include 1, 2, and 3 periods of short training sequence, respectively.

[0082] It should be noted that the detected signal is delayed by three different first delay durations by the first delay unit 121, and then the detected signal and each basic delay signal are autocorrelation calculated by the first autocorrelation unit 122. The average value is delayed by three different first delay durations by the reference delay unit 113, and then the average value and each delay value are autocorrelation calculated by the reference autocorrelation unit 114. The reference value indicates the reference energy value. In this way, the energy measured within the same time window and the correlation value need to use the same or aligned data segments to make the energy correspond and the reference value referential, thereby making the detection result more accurate.

[0083] In some embodiments, such as Figure 3 As shown, the difference module 14 may include multiple difference units 141, and the number of related submodules 131 is equal to the number of difference units 141; wherein: Each numerator unit 141 is used to receive a first value and a corresponding second value, perform difference processing on the first value and the second value, and obtain a difference value.

[0084] It should be noted that each difference unit 141 is used to perform difference processing on the first value and a second value generated by a related submodule 131 to obtain a difference value.

[0085] In some embodiments, such as Figure 3As shown, the detection module 15 may include a logic processing unit 151 and multiple comparison and detection units 152, wherein the number of related sub-modules 131 is equal to the number of comparison and detection units 152; wherein: Each comparison and detection unit 152 is used to compare the reference value and the corresponding difference value, and when the difference value is greater than the reference value, to perform plateau peak detection processing on the difference between the difference value and the reference value to obtain the detection value; The logic processing unit 151 is configured to determine that a short training sequence has been detected when any one of the multiple detection values ​​is in a first level state; or, when all detection values ​​are in a second level state, determine that a short training sequence has not been detected.

[0086] For example, when the second autocorrelation module 13 includes two correlation sub-modules 131, the detection module 15 includes two comparison and detection units 152.

[0087] like Figure 3 As shown, each comparison and detection unit 152 receives a reference value and a corresponding difference value, and the logic processing unit 151 receives multiple detection values.

[0088] It should be noted that the difference between the differential value and the reference value is specifically the difference obtained by subtracting the reference value from the differential value. That is, the comparison and detection unit 152 performs plateau peak detection processing on the portion of the differential value exceeding the reference value. When the differential value is greater than the reference value, the difference obtained by subtracting the reference value from the differential value is greater than 0, and the comparison and detection unit 152 performs plateau peak detection processing on the difference obtained in this case. When the differential value is less than the reference value, the difference obtained by subtracting the reference value from the differential value is less than 0, and the comparison and detection unit 152 does not perform plateau peak detection processing on the difference obtained in this case. Here, the plateau peak is not a sharp single-point peak, but rather a flat or gradually varying continuous high-value region. When the received signal is autocorrelated with a copy delayed by one symbol length, a flat-topped peak region will form near the beginning of the symbol. The plateau peak detection processing aims to identify the existence of this flat region.

[0089] In this embodiment, plateau peak detection processing is performed on the difference between the difference value and the reference value. Only the sample points in the difference value that are higher than the reference value are retained, while the part that is lower is ignored or set to zero. In this way, the influence of the signal strength of the detected signal on the peak value can be eliminated, and the detection value calculated by the signal with different strengths can be kept stable.

[0090] In some embodiments, the logic processing unit 151 is used to perform OR logic processing on multiple detection values ​​to obtain a detection result.

[0091] In this way, as long as one detection value is in the first level state, the data packet is determined to have arrived, thereby improving detection sensitivity and reducing the probability of missed detection.

[0092] It should be noted that if the second autocorrelation module 13 includes only one correlation submodule 131, that is, the detection module 15 includes only one comparison and detection unit 152, the comparison and detection unit 152 generates one detection value, and the logic processing unit 151 is used to receive the detection value. When the detection value is in the first level state, it is determined that a short training sequence has been detected; or, when the detection value is in the second level state, it is determined that no short training sequence has been detected.

[0093] The first level state involved in the embodiments of this disclosure and the following description can be a high level state (logic "1"), and the second level state can be a low level state (logic "0").

[0094] In some embodiments, such as Figure 3 As shown, the comparison and detection unit 152 is also used to receive an enable signal (which can be represented by Valid), and when the enable signal is in the enabled state, compare the reference value and the difference value and perform plateau peak detection processing on the difference between the difference value and the reference value.

[0095] In other words, when the enable signal is enabled, the comparison and detection unit 152 is turned on and in operation; when the enable signal is disabled, the comparison and detection unit 152 is turned off and not in operation, and does not compare the reference value and the difference value, nor does it perform plateau peak detection processing on the difference between the difference value and the reference value. Thus, the comparison and detection unit 152 can be turned off when it is not needed, saving energy.

[0096] See Figure 4 This illustrates a schematic diagram of the framework of a detection device provided in an embodiment of this disclosure. Figure 4 As shown, Z(K) represents the detected signal, SUM represents coherent superposition, Trunc 4 bits represents truncation, ||U|| represents complex number calculation, and the reset calculation specifically involves modulus approximation. In the first autocorrelation module 12: Z -1 Z represents a delay of 1 data unit. -16This indicates a delay of 16 data units, where one data unit is one sampling point (50ns), and 16 data units are 16 sampling points (800ns). AC0 represents the autocorrelation calculation of the detected signal and the base delayed signal obtained by delaying the detected signal by 800ns; AC1 represents the autocorrelation calculation of the detected signal and the base delayed signal obtained by delaying the detected signal by 1600ns; and AC2 represents the autocorrelation calculation of the detected signal and the base delayed signal obtained by delaying the detected signal by 2400ns. The second autocorrelation module 13 includes two correlation submodules 131 (which can be represented as 131-1 and 131-2 respectively). In correlation submodule 131-1: Z -K1 Indicates a delay of K1ns, Z -16 This indicates a delay of 16 data units (i.e., 800 ns); AC0' represents the autocorrelation calculation of the detected signal and the interference delay signal obtained by delaying the detected signal by K1 ns; AC1' represents the autocorrelation calculation of the detected signal and the interference delay signal obtained by delaying the detected signal by (K1+800) ns; AC2' represents the autocorrelation calculation of the detected signal and the interference delay signal obtained by delaying the detected signal by (K1+1600) ns. In the correlation submodule 131-2: Z -K2 Indicates a delay of K2ns, Z -16 This indicates a delay of 16 data units (i.e., 800 ns); "AC0" indicates autocorrelation calculation of the detected signal and the interference delay signal obtained by delaying the detected signal by K2 ns; "AC1" indicates autocorrelation calculation of the detected signal and the interference delay signal obtained by delaying the detected signal by (K2+800) ns; "AC2" indicates autocorrelation calculation of the detected signal and the interference delay signal obtained by delaying the detected signal by (K2+1600) ns. In the reference value generation module 11: Z -16 The values ​​represent a delay of 16 data units (i.e., 800 ns); AC0 represents the autocorrelation calculation performed on the average value and the delayed value obtained by delaying the average value by 800 ns; AC1 represents the autocorrelation calculation performed on the average value and the delayed value obtained by delaying the average value by 1600 ns; AC2 represents the autocorrelation calculation performed on the average value and the delayed value obtained by delaying the average value by 2400 ns; and the reference value is obtained by truncating the values ​​obtained after adding and transforming multiple autocorrelation values.

[0097] It should be noted that, Figure 4 The number of bits for each signal or value (e.g., 8 bits, 17 bits, 19 bits, and 23 bits) are examples and are not specifically limited.

[0098] This embodiment provides a novel autocorrelation detection structure. Specifically, (1) in the base path (i.e., the first autocorrelation module 12): the initial detection signal is sampled by the ADC and downsampled to a 20MHz baseband sampling rate. The current data (i.e., the detected signal) and the data obtained after delaying the current data by 800ns, 1600ns and 2400ns (i.e., multiple base delay signals) are autocorrelated and coherently superimposed. Then, a moving average processing with a window of 800ns is performed, and abs is taken as the "minuend" of the difference structure; (2) in the diff1 path (i.e., the correlation submodule 131-1): the current data and the data obtained after delaying the current data by K1ns, (K1+800)ns and (K1+1600)ns (i.e., multiple interference delay signals) are autocorrelated. Similarly, a moving average processing with a window of 800ns is performed, and abs is taken as the "minuend 1" of the difference structure; (3) in the diff2 path (i.e., the first autocorrelation module 12): the current data and the data obtained after delaying the current data by K1ns, (K1+800)ns and (K1+1600)ns (i.e., multiple interference delay signals) are autocorrelated. The moving average processing with a window of 800ns is performed, and abs is taken as the "minuend 1" of the difference structure; (3) in the diff2 path (i.e., the first autocorrelation module 12): the first autocorrelation module 12 is autocorrelation and the second autocorrelation module 12 is autocorrelation and the third autocorrelation module 12 is autocorrelation and the fourth autocorrelation module 12 is autocorrelation and the fifth autocorrelation module 12 is autocorrelation and the sixth autocor In path (related submodule 131-2): the current data and the data obtained after delaying the current data by K2ns, (K2+800)ns and (K2+1600)ns (i.e., multiple interference delay signals) are autocorrelation calculated, and the moving average processing with a window of 800ns is also performed. Then, abs is taken as the difference structure "subtraction 2"; (4), in reference In the path (i.e., reference value generation module 11): the current data directly takes abs, and then performs a moving average processing with a window of 800ns to obtain the average value. The average value and the data obtained after delaying the average value by 800ns, 1600ns and 2400ns (i.e. multiple interference values) are autocorrelated and superimposed. At the same time, a scaling factor is multiplied and then truncated as a reference value; (5) the difference is obtained based on the result of (1) (i.e. the first value) and the result of (2) (i.e. the second value generated by the correlation submodule 131-1). A difference value is obtained. The part of the difference value that exceeds (4) (i.e. the reference value) (i.e. the difference value) is processed by plateau peak detection; (6) the difference is obtained based on the result of (1) and the result of (3) (i.e. the second value generated by the correlation submodule 131-2). Another difference value is obtained. The part of the difference value that exceeds (4) is processed by plateau peak detection; (7) the above two results are ORed and output to indicate that the data packet header has been detected. Furthermore, the detection results can be further confirmed through simulation results of narrowband interference such as Bluetooth Low Energy (BLE). The detection device 10 can overcome the limitations of using autocorrelation detection to capture multi-antenna data packets, effectively eliminating false alarms caused by single-tone and narrowband interference while ensuring packet detection requirements and detection probability. It effectively improves the performance of multi-antenna packet detection and effectively compensates for the packet loss problem of cross-correlation detection in multi-antenna cases.

[0099] In another embodiment of this disclosure, participants Figure 5 This illustrates a flowchart of a detection method provided in an embodiment of this disclosure. Figure 5 As shown, the method may include: S201: Receive the detected signal and generate a reference value based on the detected signal. The reference value indicates the reference energy value.

[0100] S202: Perform autocorrelation calculation and moving average processing based on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of the short training sequence.

[0101] S203: Perform autocorrelation calculation and moving average processing based on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration being not an integer multiple of the period of the short training sequence.

[0102] S204: Perform a difference operation on the first value and at least one second value to obtain at least one difference value.

[0103] S205: Compare the reference value with at least one difference value to obtain the detection result.

[0104] This disclosure provides a detection method, specifically an autocorrelation detection method for eliminating false alarms caused by single-tone signals and narrowband signals. This detection method is applied to the detection device 10 in the aforementioned embodiment.

[0105] It should be noted that the labels of steps S201 to S205 are not used to limit the order in which the steps are executed. For example, step S202 may be executed before step S203, or step S203 may be executed before step S202, or steps S202 and S203 may be executed simultaneously.

[0106] In some embodiments, comparing a reference value with at least one difference value to obtain a detection result may include: When the difference value is greater than the reference value, it is determined that a short training sequence has been detected; or, when the difference value is less than the reference value, it is determined that no short training sequence has been detected.

[0107] In some embodiments, the method may further include: The initial detection signal is subjected to analog-to-digital conversion and downsampling to obtain the detection signal.

[0108] In some embodiments, performing autocorrelation calculation and moving average processing based on the detected signal and at least one fundamental delay signal to obtain a first value may include: By delaying the detected signal by multiple different first delay durations, multiple basic delay signals are obtained; Autocorrelation is calculated on the detected signal and each fundamental delay signal to obtain multiple first autocorrelation signals; The first autocorrelation signal is obtained by coherently superimposing multiple first autocorrelation signals. The first superimposed signal is processed by a moving average of the period of a short training sequence within a window to obtain the first average signal; The first average signal is subjected to complex number calculations to obtain the first value.

[0109] In some embodiments, the method may further include: A second value is generated by the relevant sub-modules based on a preset second delay duration; The value of the second delay duration varies in different related sub-modules.

[0110] It should be noted that step S203 is implemented by at least one correlation submodule 131, and each correlation submodule 131 generates a second value. For each correlation submodule 131, the detected signal is received, and the second value is obtained by performing autocorrelation calculation and moving average processing based on the detected signal and at least one interference delay signal.

[0111] Specifically, in some embodiments, the second value is obtained by performing autocorrelation calculation and moving average processing based on the detected signal and at least one interference delay signal, which may include: The detected signal is delayed by multiple different second delay durations to obtain multiple interference delay signals; wherein the delay duration of two adjacent interference delay signals differs by a period of the training sequence. Autocorrelation calculations are performed on the detected signal and each interference delay signal to obtain multiple second autocorrelation signals; Multiple second autocorrelation signals are coherently superimposed to obtain a second superimposed signal; The second superimposed signal is processed by a moving average of the period of a short training sequence within a window to obtain the second average signal; The second average signal is subjected to complex number calculations to obtain the second value.

[0112] In some embodiments, generating a reference value based on the detected signal may include: Perform complex number calculations on the detected signal to obtain an intermediate value; The median value is processed by a moving average with a window of short training sequence periods to obtain the average value; By delaying the average value by multiple different first delay durations, multiple delay values ​​are obtained; Autocorrelation was calculated for the average value and each delay value separately to obtain multiple autocorrelation values; Multiple autocorrelation values ​​are added together and numerically transformed to obtain a reference value.

[0113] In some embodiments, comparing a reference value with at least one difference value to obtain a detection result may include: The reference value and the corresponding difference value are compared. If the difference value is greater than the reference value, the difference between the difference value and the reference value is processed by plateau peak detection to obtain the detection value. When any detection value is in the first level state, it is determined that a short training sequence has been detected; or, when all detection values ​​are in the second level state, it is determined that no short training sequence has been detected.

[0114] In some embodiments, the number of basic delay signals is equal to the number of delay values.

[0115] For details not disclosed in the embodiments of this disclosure, please refer to the description of the foregoing embodiments for understanding.

[0116] This disclosure provides a novel autocorrelation differential structure detection algorithm that effectively eliminates false alarms caused by interference from single-tone signals and narrowband signals while ensuring packet detection requirements and detection probability. It effectively improves the packet detection performance of multi-antenna systems and effectively compensates for packet loss in cross-correlation detection under multi-antenna conditions.

[0117] Understandably, in this embodiment, a "unit" can be a portion of a circuit, a portion of a processor, a portion of a program or software, etc., and can also be a module or a non-modular component. Furthermore, the components in this embodiment can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional module.

[0118] If the integrated unit is implemented as a software functional module and not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or 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.) or processor to execute all or part of the steps of the method described in this embodiment. 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.

[0119] Therefore, this embodiment provides a computer-readable storage medium storing a computer program that, when executed by at least one processor, implements the steps of any of the detection methods described in the foregoing embodiments.

[0120] This embodiment also provides a computer program product, which includes a computer program that, when executed by at least one processor, implements the steps of any of the detection methods described in the foregoing embodiments.

[0121] Based on the above description of the composition of the detection device 10, the computer-readable storage medium, and the computer program product, see [link to relevant documentation]. Figure 6 It illustrates a structural schematic of an electronic device provided in an embodiment of this disclosure. Figure 1 .like Figure 6 As shown, electronic device 30 may include: a communication interface 301, a memory 302, and a processor 303; the various components are coupled together via a bus system 304. It is understood that the bus system 304 is used to implement communication between these components. In addition to a data bus, the bus system 304 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 6 All buses are labeled as bus system 304. Among them, communication interface 301 is used for receiving and sending signals during information exchange with other external network elements; Memory 302 is used to store computer programs that can run on processor 303; The processor 303 is configured to perform the steps of the aforementioned detection method when running the computer program.

[0122] It is understood that the memory 302 in this embodiment can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 302 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0123] The processor 303 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 303 or by software instructions. The processor 303 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 302, and the processor 303 reads the information in memory 302 and, in conjunction with its hardware, completes the steps of the above method.

[0124] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0125] For software implementation, the techniques described herein can be achieved through modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented within the processor or externally.

[0126] Alternatively, as another embodiment, the processor 303 is also configured to perform the method described in any of the foregoing embodiments when running the computer program.

[0127] In yet another embodiment of this disclosure, see [link to relevant documentation]. Figure 7 It illustrates a structural schematic of an electronic device provided in an embodiment of this disclosure. Figure 2 .like Figure 7 As shown, the electronic device 30 includes at least the detection device 10 described in any of the foregoing embodiments.

[0128] For details not disclosed in the embodiments of this disclosure, please refer to the description of the foregoing embodiments for understanding.

[0129] The above description is merely a preferred embodiment of this disclosure and is not intended to limit the scope of protection of this disclosure.

[0130] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover 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. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0131] The sequence numbers of the embodiments disclosed above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0132] The methods disclosed in the several method embodiments provided in this disclosure can be arbitrarily combined without conflict to obtain new method embodiments.

[0133] The features disclosed in the several product embodiments provided in this disclosure can be combined arbitrarily without conflict to obtain new product embodiments.

[0134] The features disclosed in the several method or device embodiments provided in this disclosure can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0135] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A detection device, characterized in that, include: A reference value generation module is used to receive the detected signal and generate a reference value based on the detected signal, wherein the reference value indicates a reference energy value; The first autocorrelation module is used to perform autocorrelation calculation and moving average processing based on the detected signal and at least one basic delay signal to obtain a first value; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of the short training sequence; The second autocorrelation module is used to perform autocorrelation calculation and moving average processing based on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration being not an integer multiple of the period of the short training sequence; A difference module is used to perform difference processing on the first value and at least one of the second values ​​to obtain at least one difference value; A detection module is used to compare the reference value with at least one of the difference values ​​to obtain a detection result.

2. The detection device according to claim 1, characterized in that, The detection module is further configured to determine that the short training sequence has been detected when the difference value is greater than the reference value; or, to determine that the short training sequence has not been detected when the difference value is less than the reference value.

3. The detection device of claim 1, wherein, The detection device further includes: The sampling module is used to perform analog-to-digital conversion and downsampling on the initial detection signal to obtain the detected signal.

4. The detection device of claim 1, wherein, The first autocorrelation module includes: The first delay unit is used to delay the detected signal by multiple different first delay durations to obtain multiple basic delay signals; The first autocorrelation unit is used to perform autocorrelation calculations on the detected signal and each of the basic delay signals to obtain multiple first autocorrelation signals; The first addition unit is used to coherently superimpose multiple first autocorrelation signals to obtain a first superimposed signal; The first moving average unit is used to perform moving average processing on the first superimposed signal with a window equal to the period of the short training sequence to obtain the first average signal. The first complex number calculation unit is used to perform complex number calculations on the first average signal to obtain the first value.

5. The detection device of claim 1, wherein, The second autocorrelation module includes at least one correlation submodule, each of which is used to generate a second value according to a preset second delay duration; The values ​​of the second delay duration are different in different related sub-modules.

6. The detection device of claim 5, wherein, Each of the relevant sub-modules includes: The second delay unit is used to delay the detected signal by multiple different second delay durations to obtain multiple interference delay signals; wherein the delay duration of two adjacent interference delay signals differs from the period of the short training sequence; The second autocorrelation unit is used to perform autocorrelation calculations on the detected signal and each of the interference delay signals to obtain multiple second autocorrelation signals; The second addition unit is used to coherently superimpose multiple second autocorrelation signals to obtain a second superimposed signal; The second moving average unit is used to perform a moving average processing on the second superimposed signal with a window being the period of the short training sequence, to obtain a second average signal. The second complex number calculation unit is used to perform complex number calculations on the second average signal to obtain the second value.

7. The detection device of claim 1, wherein, The reference value generation module includes: A reference complex number calculation unit is used to perform complex number calculations on the detected signal to obtain an intermediate value; A reference moving average unit is used to perform a moving average processing on the intermediate value with a window of the period of the short training sequence to obtain the average value; A reference delay unit is used to delay the average value by multiple different first delay durations to obtain multiple delay values; A reference autocorrelation unit is used to perform autocorrelation calculations on the average value and each of the delay values ​​to obtain multiple autocorrelation values; The reference addition unit is used to perform addition calculations and numerical transformations on multiple autocorrelation values ​​to obtain the reference value.

8. The detection device of claim 5, wherein, The detection module includes a logic processing unit and multiple comparison and detection units, wherein the number of related sub-modules is equal to the number of comparison and detection units; wherein: Each of the comparison and detection units is used to compare the reference value and the corresponding difference value, and when the difference value is greater than the reference value, to perform plateau peak detection processing on the difference between the difference value and the reference value to obtain a detection value; The logic processing unit is configured to determine that the short training sequence has been detected when any of the detection values ​​is in a first level state; or, when all the detection values ​​are in a second level state, determine that the short training sequence has not been detected.

9. The detection device of claim 7, wherein, The number of the basic delay signals is equal to the number of the delay values.

10. A method of detection, characterized in that, include: Receive the detected signal and generate a reference value based on the detected signal, the reference value indicating a reference energy value; A first value is obtained by performing autocorrelation calculation and moving average processing on the detected signal and at least one basic delay signal; the basic delay signal is obtained by delaying the detected signal by a first delay duration, the first delay duration being an integer multiple of the period of the short training sequence; Autocorrelation calculation and moving average processing are performed on the detected signal and at least one interference delay signal to obtain at least one second value; the interference delay signal is obtained by delaying the detected signal by a second delay duration, the second delay duration being not an integer multiple of the period of the short training sequence; The first value and at least one of the second values ​​are differentially processed to obtain at least one difference value; The reference value and at least one of the difference values ​​are compared to obtain the detection result.

11. The detection method according to claim 10, characterized in that, The detection result is obtained by comparing the reference value with at least one of the difference values, including: When the difference value is greater than the reference value, it is determined that the short training sequence has been detected; or, when the difference value is less than the reference value, it is determined that the short training sequence has not been detected.

12. The detection method of claim 10, wherein, The method further includes: The initial detection signal is subjected to analog-to-digital conversion and downsampling to obtain the detected signal.

13. An electronic device, comprising: Includes memory and processor, wherein: The memory is used to store computer programs that can run on the processor; The processor is configured to perform the method as described in any one of claims 10 to 12 when running the computer program.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by at least one processor, implements the method as described in any one of claims 10 to 12.

15. A computer program product, characterised in that, The computer program product includes a computer program that, when executed by at least one processor, implements the method as described in any one of claims 10 to 12.

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