A method, system, device and medium for detecting a DSSS data packet

Abstract

This invention relates to a method, system, device, and medium for detecting DSSS data packets. The method includes: receiving a radio frequency signal transmitted by a transmitter and preprocessing it to obtain a baseband discrete received signal sequence; performing differential processing on the baseband discrete received signal sequence to generate a differential periodic signal; generating a local reference sequence matching the differential periodic signal; performing a cross-correlation operation on the differential periodic signal using the local reference sequence, and accumulating the coherent energy of the cross-correlation operation results over multiple periods to obtain a correlation metric; delaying and accumulating the differential periodic signal to obtain an interference metric; introducing a first decision threshold corresponding to the correlation metric and a second decision threshold corresponding to the interference metric, and outputting a decision result indicating that a DSSS data packet has been detected based on a dual-threshold hierarchical mechanism. Compared with existing technologies, this invention can improve the performance of DSSS data packet detection and reduce the false alarm probability in interference environments without traversing the polarity combinations of preamble bits.

Description

Technical Field

[0001] This invention relates to the fields of wireless communication and digital signal processing technology, and in particular to a DSSS packet detection method, system, device and medium. Background Technology

[0002] In recent years, with the rapid development of Wireless Local Area Network (Wi-Fi) technology, Wi-Fi products based on the IEEE 802.11 series of standards have been widely used in various application scenarios such as mobile computing, the Internet of Things (IoT), and high-speed internet access. Among them, the IEEE 802.11b standard, as one of the important early commercialized Wi-Fi technologies, operates in the 2.4 GHz band and uses Direct Sequence Spread Spectrum (DSSS) modulation, providing data transmission rates of up to 11 Mbps. Although subsequent Wi-Fi standards have continuously evolved in terms of speed and spectral efficiency, the DSSS system adopted by 802.11b still has certain research value and engineering significance in specific historical stages and in some application scenarios with high requirements for low cost, low power consumption, and compatibility due to its simple implementation and strong anti-interference capabilities.

[0003] Direct Sequence Spread Spectrum (DSSS) communication broadens the data signal in the frequency domain through spreading codes, exhibiting excellent anti-interference capabilities and low interception probability. It is widely used in wireless LANs, the Internet of Things (IoT), and anti-interference communication systems. In communication systems employing DSSS technology, the receiver must first achieve time-frequency synchronization with the transmitted signal before demodulating the data. This crucial process typically relies on reliable detection and capture of the synchronization domain (SYNC) of the preamble in the physical layer frame structure. At the DSSS receiver, packet detection usually depends on correlation detection of the preamble to determine the arrival time of the data packet. In practical communication environments, the received signal of a DSSS packet often exhibits the following characteristics: Firstly, due to carrier frequency offset, phase noise, and multipath effects, the received signal introduces frequency offset and phase rotation between different preamble bits; secondly, the preamble typically consists of multiple bits with variable polarity, requiring the receiver to traverse different polarity combinations during coherent correlation detection, significantly increasing computational complexity and degrading detection performance under low signal-to-noise ratio conditions. Furthermore, due to the openness and diversity of devices in the 2.4GHz ISM band, periodic interference signals (such as microwave ovens, Bluetooth devices, and wireless cameras) are a typical problem in the 802.11b environment, which can lead to preamble detection failure.

[0004] In the prior art, in order to eliminate the influence of frequency offset, frequency offset estimation and compensation are usually required, or incoherent detection methods are used. However, the above methods are either highly complex to implement or have limited detection performance.

[0005] Therefore, a new DSSS packet detection method is needed to improve DSSS packet detection performance and reduce the false alarm probability in interference environments without explicit frequency offset estimation and by reducing dependence on preamble polarity combinations. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology by providing a DSSS packet detection method, system, device, and medium. It achieves high-performance DSSS packet detection without explicit frequency offset estimation and polarity traversal, and suppresses false alarms caused by other periodic interference signals through delay accumulation. The objective of this invention can be achieved through the following technical solutions: According to a first aspect of the present invention, a DSSS packet detection method is provided, comprising: The system receives the radio frequency signals transmitted by the transmitter and preprocesses them to obtain a discrete baseband received signal sequence. The baseband discrete received signal sequence is subjected to differential processing of delay conjugate multiplication to generate differential periodic signals within the duration of multiple preamble bits; Generate a local reference sequence that matches the differential periodic signal; The local reference sequence is used to perform cross-correlation operation on the differential periodic signal, and the cross-correlation operation results are accumulated with coherent energy over multiple periods to obtain the correlation metric. The differential periodic signal is delayed and accumulated to obtain the interference measurement value; Introducing a first decision threshold corresponding to the relevant metric value and a second decision threshold corresponding to the interference metric value, and based on a dual-threshold hierarchical mechanism, outputting the decision result of detecting DSSS data packets.

[0007] Preferably, the preprocessing includes sequential down-conversion, filtering, and analog-to-digital conversion.

[0008] Preferably, generating a local reference sequence that matches the differential periodic signal specifically includes: 1) Initialize the 11-chip Buck sequence Its delayed 1-times Barker sequence ; 2) According to the Buck sequence Calculate the sequence length as The original reference sequence The expression is: , in, For Unit sampling rate Regarding integer multiples of 11 ; 3) Based on the original reference sequence ,pass , Calculate the single-bit reference sequence using the element index. The expression is: , 4) Use a single-bit reference sequence The local reference sequence is obtained by repeatedly representing a reference sequence of multiple bits. ,in, For element index.

[0009] Preferably, generating a local reference sequence that matches the differential periodic signal specifically includes: 1) Initialize the 11-chip Buck sequence Its delayed 1-times Barker sequence ; 2) According to the Buck sequence Calculate the sequence length as The original reference sequence The expression is: , in, For Unit sampling rate Regarding integer multiples of 11 ; 3) Based on the original reference sequence ,pass , Using the element index, calculate the initial single-bit reference sequence, and retain only the Barker sequence elements from the initial single-bit reference sequence to obtain the single-bit reference signal. The expression is: ; 4) Use a single-bit reference sequence The local reference sequence is obtained by repeatedly representing a reference sequence of multiple bits. ,in, For element index.

[0010] Preferably, the single-bit reference signal The last element in the array is set to 0.

[0011] Preferably, after performing coherent energy accumulation on the cross-correlation calculation results over multiple periods, the method further includes normalization processing to obtain a correlation metric; the method of delaying and accumulating the differential periodic signal further includes normalization processing to obtain an interference metric.

[0012] Preferably, the step of introducing a first decision threshold corresponding to the relevant metric value and a second decision threshold corresponding to the interference metric value, and outputting a decision result for detecting DSSS data packets based on a dual-threshold hierarchical mechanism, specifically includes: Scenario 1: When When this occurs, it is determined that a DSSS data packet has been detected; among which, For relevant metrics, This is a measure of interference. , As the first judgment threshold, This is the second judgment threshold. and This is the preset decision margin parameter; Scenario 2: When At that time, it was determined that no DSSS data packets were detected; Case 3: If neither Case 1 nor Case 2 applies, construct the extended feature vector. As input, a pre-trained classification model is used to output the decision result.

[0013] According to a second aspect of the present invention, a DSSS packet detection system is provided, comprising a transmitter and a receiver, wherein the receiver comprises: The signal receiving and processing module is used to receive the wireless radio frequency signals transmitted by the transmitter and preprocess them to obtain the baseband discrete received signal sequence. The differential periodic signal construction module is used to perform differential processing on the baseband discrete received signal sequence to generate differential periodic signals within the duration of multiple preamble bits; The local reference sequence generation module is used to generate a local reference sequence that matches the differential periodic signal; The correlation and accumulation module is used to perform cross-correlation operation on the differential periodic signal after differential using the local reference sequence, and to accumulate the coherent energy of the cross-correlation operation result over multiple periods to obtain the correlation metric value. The interference detection module is used to delay and accumulate the differential periodic signal to obtain an interference measurement value. The dual-threshold decision module is used to compare the relevant metric value and the interference metric value with the first decision threshold and the second decision threshold respectively based on the combined dual-threshold hierarchical mechanism, and output the decision result of whether DSSS data packets are detected based on the comparison result.

[0014] According to a third aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement any of the methods described above.

[0015] According to a fourth aspect of the invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements any of the methods described herein.

[0016] Compared with the prior art, the present invention has the following advantages: (1) This invention converts the aperiodic received signal into a periodic signal with no frequency offset between elements through differential conversion, so that the signal no longer has polarity within each preamble bit time, eliminating the influence of preamble polarity and frequency offset. Furthermore, it utilizes the periodic structure for coherent correlation accumulation, achieving high-performance DSSS packet detection without explicit frequency offset estimation and polarity traversal. It also suppresses false alarms caused by other periodic interference signals through delayed accumulation. This invention utilizes the periodicity of the signal for interference detection, maintaining a low false alarm probability even in interference scenarios, while not affecting the detection probability of the DSSS signal.

[0017] (2) The present invention designs a local reference sequence that matches the differential periodic signal. This sequence is not affected by the polarity of the preamble bits and does not need to traverse all the polarity combinations of the preamble bits. It can directly perform coherent energy accumulation and merging to improve the performance of cross-correlation detection.

[0018] (3) Considering that the last element of each period of the periodic signal is not periodic and is not suitable for coherent accumulation, in the process of designing the local reference sequence, the last element of the constructed single-bit reference signal can be set to 0, which ensures the accuracy of coherent accumulation calculation and improves the accuracy of DSSS data packet detection.

[0019] (4) Considering that the correlation metric and the interference metric are large values ​​close to 1 and small values ​​close to 0 respectively, a dual threshold grading mechanism is introduced to make DSSS data packet detection decisions. When the two values ​​do not fall into the grading interval, a classification model is introduced. By jointly modeling the correlation metric, the interference metric and their corresponding threshold and margin parameters, the nonlinear coupling relationship between "correlation-interference-threshold-margin" is learned, and adaptive decision optimization for different signal-to-noise ratios and interference conditions is realized, thereby effectively reducing the false alarm probability and improving the detection probability. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the DSSS packet detection system architecture of the present invention; Figure 3 This is a schematic diagram comparing the DSSS preamble signals before and after differential processing. Figure 4 This is a schematic diagram of periodic reference sequence matching and coherent accumulation. Figure 5 This is a schematic diagram of periodic reference sequence matching and coherent accumulation.

[0021] Figure 6 This is a schematic diagram illustrating the effect of the metric value c(n) at a certain sampling point.

[0022] Figure 7 For performance comparison. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] Example This embodiment provides a DSSS packet detection method, such as Figure 1 As shown, the method includes: S1. Receive the radio frequency signal transmitted by the transmitter. Preprocessing yields the baseband discrete received signal sequence. .

[0025] In this embodiment, the wireless radio frequency signal transmitted by the receiving transmitter is... The preprocessing steps are down-conversion, filtering, and analog-to-digital conversion, and the calculation expression is as follows: , in, Indicates carrier frequency offset, The sampling period is For the initial phase, It is additive white Gaussian noise.

[0026] In the preamble of the DSSS data packet, the radio frequency signal Represented as spreading code With preamble bit polarity The product form is expressed as: ,in, .

[0027] S2, for the baseband discrete received signal sequence Perform differential processing using delayed conjugate multiplication to eliminate polarity, generating a differential periodic signal over multiple preamble bit durations. This converts the aperiodic received signal into a periodic signal with no frequency offset between elements.

[0028] Differential periodic signal after differentiation The calculation expression is: , in, express . conjugate.

[0029] Specifically, baseband discrete received signal sequence It is a non-differential periodic signal related to the preamble bits, while a differential periodic signal... It is a near-differential periodic signal independent of the preamble bits, and its period length is... With sampling rate related.

[0030] When sampling rate At that time, the period length = , It is an integer.

[0031] Differential periodic signal Except for the last element of each cycle, which is related to the preamble bit and no longer has periodicity.

[0032] Figure 4 This is a schematic diagram comparing the DSSS preamble signals before and after differential processing.

[0033] It should be noted that although there are schemes for differential processing of signals at the receiving end, the differential processing at the receiving end is mainly a dual operation to the differential processing at the transmitting end. The differential processing of this invention is proposed to address the inability of the receiving end to obtain the gain of combined detection due to the bipolarity of DSSS data symbols. There is no differential processing at the transmitting end in this invention, that is, the problems solved are different.

[0034] S3, Generation and Differential Periodic Signal Matching local reference sequence .

[0035] In this embodiment, an 11-chip Buck sequence is defined. Its sequence after a 1-time delay is also a Buck sequence. .

[0036] S3-1. Calculate the single-bit reference signal .

[0037] Define a single-bit reference sequence as: ,in The sequence length is The original reference signal sequence, For element index.

[0038] Original reference signal sequence , is represented as: ; Reference signal , is represented as: , This calculation method has higher energy, more prominent peak values, and more obvious detection threshold discrimination, thus it has stronger false alarm suppression capability and better system robustness; Alternatively, using only the Barker sequence elements, it can be represented as: .

[0039] This calculation method, due to its abundance of zero elements and sparse sequence, can filter out some periodic interference and requires less hardware storage and computation.

[0040] Different single-bit reference signals are selected according to the needs of practical application scenarios. Calculation method.

[0041] (1) When the sampling rate hour, and The sequence lengths are all ,have: , , Differential periodic signal The last element of each period is aperiodic and unsuitable for coherent accumulation; therefore, the reference signal is... Setting the last element to 0 results in: .

[0042] (2) When the sampling rate hour, and The sequence lengths are all ,have: , , or, .

[0043] S3-2, Calculate the multi-bit local reference sequence .

[0044] Using a single-bit reference sequence The local reference sequence is obtained by repeatedly representing a reference sequence of multiple bits. , is represented as: ,in, Corresponding to the signal point number in the local reference sequence, such as Figure 5 As shown.

[0045] S4. Calculate relevant metrics. and interference measurement value .

[0046] S4-1, Using a local reference sequence For differential periodic signals Perform cross-correlation calculations and accumulate the coherent energy of the cross-correlation results over multiple periods to obtain the correlation metric. .

[0047] Differential periodic signal Matching local reference sequence Window length is The sliding cross-correlation was calculated and normalized to obtain the correlation metric at each sample point. : .

[0048] For 802.11b preamble signals, the correlation metric is... exist It obtains a large value close to 1. Figure 6 This is a schematic diagram of the effect of the metric value c(n) at a certain sampling point. It can be seen that the correlation peak value has a significant gain compared to the previous one during the detection process of this invention.

[0049] S4-2, Differential periodic signal The interference metric is obtained by accumulating delays and normalizing the results. .

[0050] In this embodiment, the differential periodic signal The interference metric is obtained by performing delay accumulation and normalization. : , in It is the delay depth.

[0051] For 802.11b preamble signals, exist The value is small and close to 0. For other periodic interference signals (with different periods) that are not part of the 802.11b preamble, Not in All values ​​are small and close to 0.

[0052] S5. Introduce relevant metrics The corresponding first judgment threshold and interference measurement value The corresponding second judgment threshold Based on a dual-threshold hierarchical mechanism, the system outputs a judgment result indicating that a DSSS data packet has been detected.

[0053] Because in At this point, relevant metrics and interference measurement value These are large values ​​close to 1 and small values ​​close to 0, respectively. Therefore, a dual-threshold decision can be made by combining the two.

[0054] The specific judgment process is as follows: Scenario 1: When When a DSSS data packet is detected, an output is generated; where, and This is the preset decision margin parameter; Scenario 2: When At that time, it was determined that no DSSS data packets were detected; Case 3: If neither Case 1 nor Case 2 applies, construct the extended feature vector. As input, a pre-trained classification model is used to output a decision result. ,in This indicates that the signal is present. This indicates that the signal does not exist; thus, while ensuring real-time performance, it improves the detection accuracy under complex interference environments; by jointly modeling the correlation metric, interference metric, and their corresponding threshold and margin parameters, the artificial intelligence model can learn the nonlinear coupling relationship between "correlation-interference-threshold-margin", and achieve adaptive decision optimization for different signal-to-noise ratios and interference conditions, thereby effectively reducing the false alarm probability and improving the detection probability.

[0055] In this embodiment, the first decision threshold Second Judgment Threshold For a pre-set fixed value, and These are the preset expected false alarm probability and expected detection probability, respectively, or obtained through adaptive updates based on channel state information.

[0056] In this embodiment, and The preset decision margin parameter is set to 0.6, which is used to characterize the width of the high-confidence decision interval. It can be designed according to the false alarm probability and detection probability of the target or adaptively optimized through training data.

[0057] Figure 7 This represents the DSSS signal detection probability under an AWGN channel. As can be seen from the figure, the detection method of this invention outperforms existing detection methods.

[0058] like Figure 2 and Figure 3 As shown, this embodiment also provides a DSSS packet detection system, including a transmitter and a receiver. The receiver includes: The signal receiving and processing module is used to receive the wireless radio frequency signals transmitted by the transmitter. Preprocessing yields the baseband discrete received signal sequence. ; The differential periodic signal construction module is used to construct baseband discrete received signal sequences. Perform differential processing to generate differential periodic signals over multiple preamble bit durations. ; The local reference sequence generation module is used to generate a differential periodic signal. Matching local reference sequence ; The correlation and accumulation module is used to utilize local reference sequences. For differential periodic signals Perform cross-correlation calculations and accumulate the coherent energy of the cross-correlation results over multiple periods to obtain the correlation metric. ; Interference detection module, used to detect differential periodic signals Perform delay accumulation to obtain the interference metric. ; The dual-threshold decision module is used to combine a dual-threshold hierarchical mechanism to determine the relevant metric values. and interference measurement value Respectively with the first judgment threshold Second Judgment Threshold The comparison is performed, and a decision on whether a DSSS packet was detected is output based on the comparison result. The electronic device of this invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0059] Multiple components in the device are connected to the I / O interface, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards (NICs), modems, and wireless transceivers. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0060] The processing unit performs the various methods and processes described above. For example, in some embodiments, the methods may be implemented as computer software programs tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute the methods by any other suitable means (e.g., by means of firmware).

[0061] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload programmable logic devices (CPLDs), and so on.

[0062] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0063] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0064] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for detecting DSSS data packets, characterized in that, include: The system receives the radio frequency signals transmitted by the transmitter and preprocesses them to obtain a discrete baseband received signal sequence. The baseband discrete received signal sequence is subjected to differential processing of delay conjugate multiplication to generate differential periodic signals within the duration of multiple preamble bits; Generate a local reference sequence that matches the differential periodic signal; The local reference sequence is used to perform cross-correlation operation on the differential periodic signal, and the cross-correlation operation results are accumulated with coherent energy over multiple periods to obtain the correlation metric. The differential periodic signal is delayed and accumulated to obtain the interference measurement value; Introducing a first decision threshold corresponding to the relevant metric value and a second decision threshold corresponding to the interference metric value, and based on a dual-threshold hierarchical mechanism, outputting the decision result of detecting DSSS data packets.

2. The DSSS packet detection method according to claim 1, characterized in that, The preprocessing includes sequential down-conversion, filtering, and analog-to-digital conversion.

3. The DSSS packet detection method according to claim 1, characterized in that, The generation of a local reference sequence that matches the differential periodic signal specifically includes: 1) Initialize the 11-chip Buck sequence Its delayed 1-times Barker sequence ; 2) According to the Buck sequence Calculate the sequence length as The original reference sequence The expression is: ， in, For Unit sampling rate Regarding integer multiples of 11 ; 3) Based on the original reference sequence ,pass , Calculate the single-bit reference sequence using the element index. The expression is: ， 4) Use a single-bit reference sequence The local reference sequence is obtained by repeatedly representing a reference sequence of multiple bits. ,in, For element index.

4. The DSSS packet detection method according to claim 1, characterized in that, The generation of a local reference sequence that matches the differential periodic signal specifically includes: 1) Initialize the 11-chip Buck sequence Its delayed 1-times Barker sequence ; 2) According to the Buck sequence Calculate the sequence length as The original reference sequence The expression is: ， in, For Unit sampling rate Regarding integer multiples of 11 ; 3) Based on the original reference sequence ,pass , Using the element index, calculate the initial single-bit reference sequence, and retain only the Barker sequence elements from the initial single-bit reference sequence to obtain the single-bit reference signal. The expression is: ； 4) Use a single-bit reference sequence The local reference sequence is obtained by repeatedly representing a reference sequence of multiple bits. ,in, For element index.

5. A DSSS packet detection method according to claim 3 or 4, characterized in that, single-bit reference signal The last element in the array is set to 0.

6. The DSSS packet detection method according to claim 1, characterized in that, After performing coherent energy accumulation on the cross-correlation results over multiple periods, the method further includes normalization processing to obtain a correlation metric; the method of delaying and accumulating the differential periodic signal further includes normalization processing to obtain an interference metric.

7. The DSSS packet detection method according to claim 1, characterized in that, The process involves introducing a first decision threshold corresponding to the relevant metric value and a second decision threshold corresponding to the interference metric value. Based on a dual-threshold hierarchical mechanism, the decision result for detecting DSSS data packets is output, specifically including: Scenario 1: When When this occurs, it is determined that a DSSS data packet has been detected; among which, For relevant metrics, This is a measure of interference. , As the first judgment threshold, This is the second judgment threshold. and This is the preset decision margin parameter; Scenario 2: When At that time, it was determined that no DSSS data packets were detected; Case 3: If neither Case 1 nor Case 2 applies, construct the extended feature vector. As input, a pre-trained classification model is used to output the decision result.

8. A system employing the DSSS packet detection method of claim 1, comprising a transmitter and a receiver, characterized in that, The receiving end includes: The signal receiving and processing module is used to receive the wireless radio frequency signals transmitted by the transmitter and preprocess them to obtain the baseband discrete received signal sequence. The differential periodic signal construction module is used to perform differential processing on the baseband discrete received signal sequence to generate differential periodic signals within the duration of multiple preamble bits; The local reference sequence generation module is used to generate a local reference sequence that matches the differential periodic signal; The correlation and accumulation module is used to perform cross-correlation operation on the differential periodic signal after differential using the local reference sequence, and to accumulate the coherent energy of the cross-correlation operation result over multiple periods to obtain the correlation metric value. The interference detection module is used to delay and accumulate the differential periodic signal to obtain an interference measurement value. The dual-threshold decision module is used to compare the relevant metric value and the interference metric value with the first decision threshold and the second decision threshold respectively based on the combined dual-threshold hierarchical mechanism, and output the decision result of whether DSSS data packets are detected based on the comparison result.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 7.

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