Target frame detection method and device based on multi-dimensional features

Abstract

The present invention discloses a target frame detection method and device based on multi-dimensional features, which relates to the field of wireless communication technology. The method comprises: after the present invention converts the received wireless radio frequency signal into a digital baseband signal, the feature parameter set used as the basis for frame detection is determined according to the digital baseband signal; according to multiple feature parameters in the feature parameter set, whether the wireless signal frame carried by the wireless radio frequency signal is the target frame is judged to obtain a judgment result. It can be seen that the present invention can determine the feature parameter set according to the digital baseband signal, and judge whether the wireless signal frame is the target frame according to the feature parameters in the feature parameter set, which is conducive to improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a target frame detection method and device based on multi-dimensional features. Background Art

[0002] The IEEE 802.11 wireless communication protocol is the current mainstream wireless local area network (WLAN) communication standard, and the widely used Wi-Fi network is implemented based on this standard. The IEEE 802.11 wireless communication protocol completes the data transmission of the wireless local area network based on the sending and detection of 802.11 frames. Therefore, for wireless communication devices that use the IEEE802.11 wireless communication protocol, reliable detection of 802.11 frames is an important part of ensuring the performance of the wireless network.

[0003] In the actual application of the IEEE 802.11 wireless communication protocol, there are a large number of wireless communication devices (such as Wi-Fi devices) that need to share a common frequency band and will interfere with each other's 802.11 frame detection, such as: adjacent channel / sub-adjacent channel interference caused by multiple Wi-Fi devices working simultaneously on their respective channels, and interference from non-Wi-Fi signals such as Bluetooth, microwave ovens, ZigBee, single tone, etc. The above interference will cause the Wi-Fi receiver to falsely detect and miss the 802.11 frame. False detection causes the Wi-Fi receiver to receive and parse non-target frames and thus miss the real target frames. Missed detection causes the Wi-Fi receiver to directly miss the real target frames. Both false detection and missed detection will cause 802.11 frame data to be retransmitted, which will lead to reduced network throughput, connection freezes, and even communication interruptions. Therefore, the detection of 802.11 frames needs to be more efficient and accurate to reduce the possibility of false detection and missed detection.

[0004] It can be seen that it is particularly important to improve the detection accuracy of 802.11 frames to reduce the probability of false detection and missed detection of 802.11 frames, thereby improving the performance of wireless networks. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a target frame detection method and device based on multi-dimensional features, which can improve the detection accuracy of target frames to reduce the probability of false detection and missed detection of target frames, thereby improving wireless network performance.

[0006] In order to solve the above technical problems, the first aspect of the present invention discloses a target frame detection method based on multi-dimensional features, the method comprising:

[0007] After converting the received wireless radio frequency signal into a digital baseband signal, determining a characteristic parameter set used as a basis for frame detection according to the digital baseband signal; the characteristic parameter set includes at least two characteristic parameters;

[0008] According to the plurality of characteristic parameters in the characteristic parameter set, it is determined whether the wireless signal frame carried by the wireless radio frequency signal is a target frame to obtain a determination result.

[0009] As an optional implementation manner, in the first aspect of the present invention, the characteristic parameter set includes at least two of a power jump characteristic, a cross-correlation peak characteristic, a cross-correlation value jump characteristic, and an adjacent channel interference characteristic;

[0010] Wherein, judging whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to the plurality of characteristic parameters in the characteristic parameter set, and obtaining a judgment result includes:

[0011] For each of the characteristic parameters, determining whether the characteristic parameter satisfies a threshold condition corresponding to the characteristic parameter, and obtaining a threshold condition determination result corresponding to the characteristic parameter;

[0012] According to the threshold condition judgment results corresponding to all the characteristic parameters, a frame header validity judgment is performed on the wireless signal frame carried by the wireless radio frequency signal to obtain a frame header validity judgment result.

[0013] As an optional implementation manner, in the first aspect of the present invention, determining a set of characteristic parameters used as a basis for frame detection according to the digital baseband signal includes:

[0014] Determine, according to the digital baseband signal and the matching characteristic parameter determination method, a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection;

[0015] Wherein, the determining of a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection according to the digital baseband signal and a matching characteristic parameter determination method includes:

[0016] Detecting a power parameter of the digital baseband signal, performing a power transition feature extraction operation on the power parameter, and obtaining a power transition feature included in a feature parameter set used as a basis for frame detection; and / or,

[0017] performing a first cross-correlation operation on the digital baseband signal and the first local reference sequence to obtain a first cross-correlation operation result, and performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection; and / or,

[0018] performing a first mutual correlation operation on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result, and performing a mutual correlation value jump feature extraction operation on the first mutual correlation operation result to obtain a mutual correlation value jump feature included in a feature parameter set used as a basis for frame detection; and / or,

[0019] A first mutual correlation operation is performed on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result; and a second mutual correlation operation is performed on the digital baseband signal and the second local reference sequence to obtain a second mutual correlation operation result; and a third mutual correlation operation is performed on the digital baseband signal and the third local reference sequence to obtain a third mutual correlation operation result; and an adjacent channel interference feature extraction operation is performed on the first mutual correlation operation result, the second mutual correlation operation result and the third mutual correlation operation result to obtain an adjacent channel interference feature included in a feature parameter set used as a basis for frame detection.

[0020] As an optional implementation manner, in the first aspect of the present invention, the second local reference sequence is obtained by forward shifting a first preset frequency component of a spectrum of the first local reference sequence; and / or,

[0021] The third local reference sequence is obtained by negatively shifting the frequency spectrum of the first local reference sequence by a second preset frequency component;

[0022] The first local reference sequence is determined according to a modulation method of the wireless signal frame.

[0023] As an optional implementation manner, in the first aspect of the present invention, the detecting the power parameter of the digital baseband signal includes:

[0024] The power of the digital baseband signal in the determined target time period is calculated by sliding to obtain a power parameter, and the power parameter calculation formula is as follows:

[0025]

[0026] Wherein, P(n) represents the power parameter from the n-L+1th sampling point to the nth sampling point of the digital baseband signal within the target time period, L represents the total number of sampling points of the digital baseband signal within the target time period, and r(ni) represents the baseband input signal of the nith sampling point of the digital baseband signal within the target time period;

[0027] And, performing a power transition feature extraction operation on the power parameter to obtain a power transition feature included in a feature parameter set used as a basis for frame detection includes:

[0028] Performing a smoothing filter operation on the power parameter to obtain a processed power parameter;

[0029] The difference between the power parameter and the processed power parameter is calculated to obtain a first difference; and the power jump feature included in the feature parameter set used as a basis for frame detection is determined according to the first difference.

[0030] As an optional implementation manner, in the first aspect of the present invention, the performing of a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection includes:

[0031] Calculating a modulus of the first cross-correlation operation result divided by a target result of the power parameter, and determining a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection according to the target result;

[0032] and / or,

[0033] The performing of a cross-correlation value jump feature extraction operation on the first cross-correlation operation result to obtain a cross-correlation value jump feature included in a feature parameter set used as a basis for frame detection includes:

[0034] Performing smoothing filtering on the modulus value of the first mutual correlation operation result to obtain a smoothing filtering result, and calculating the difference between the modulus value of the first mutual correlation operation result and the modulus value of the smoothing filtering result to obtain a second difference value; and determining the mutual correlation value jump feature included in the feature parameter set used as a basis for frame detection according to the second difference value;

[0035] and / or,

[0036] The performing of the adjacent channel interference feature extraction operation on the first mutual correlation operation result, the second mutual correlation operation result, and the third mutual correlation operation result to obtain the adjacent channel interference feature included in the feature parameter set used as a basis for frame detection includes:

[0037] A first result is obtained by dividing the modulus of the first mutual correlation operation result by the second mutual correlation operation result, and a second result is obtained by dividing the modulus of the first mutual correlation operation result by the third mutual correlation operation result, and adjacent channel interference characteristics included in a feature parameter set used as a basis for frame detection are determined based on the maximum value of the first result and the second result.

[0038] As an optional implementation manner, in the first aspect of the present invention, the calculation formula corresponding to the first cross-correlation operation is as follows:

[0039]

[0040] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_0M(i) represents the ith value in the first local reference sequence, M represents the sequence length of the first local reference sequence, C_0M(n) represents the first cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate;

[0041] and / or,

[0042] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0043]

[0044] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_PM(i) represents the ith value in the second local reference sequence, M represents the sequence length of the second local reference sequence, C_PM(n) represents the second cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof;

[0045] and / or,

[0046] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0047]

[0048] Among them, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_NM(i) represents the i-th value in the third local reference sequence, M represents the sequence length of the third local reference sequence, C_NM(n) represents the third cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate.

[0049] A second aspect of the present invention discloses a target frame detection device based on multi-dimensional features, the device comprising:

[0050] A determination module, configured to determine a characteristic parameter set used as a basis for frame detection according to the digital baseband signal after converting the received wireless radio frequency signal into a digital baseband signal; the characteristic parameter set includes at least two characteristic parameters;

[0051] The judgment module is used to judge whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to a plurality of the characteristic parameters in the characteristic parameter set, and obtain a judgment result.

[0052] As an optional implementation manner, in the second aspect of the present invention, the characteristic parameter set includes at least two of a power jump characteristic, a cross-correlation peak characteristic, a cross-correlation value jump characteristic, and an adjacent channel interference characteristic;

[0053] The judgment module judges whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to the plurality of characteristic parameters in the characteristic parameter set, and obtains a judgment result, and the specific method includes:

[0054] For each of the characteristic parameters, determine whether the characteristic parameter satisfies a threshold condition corresponding to the characteristic parameter, and obtain a threshold condition determination result corresponding to the characteristic parameter;

[0055] According to the threshold condition judgment results corresponding to all the characteristic parameters, a frame header validity judgment is performed on the wireless signal frame carried by the wireless radio frequency signal to obtain a frame header validity judgment result.

[0056] As an optional implementation manner, in the second aspect of the present invention, the determination module determines a set of characteristic parameters used as a basis for frame detection according to the digital baseband signal, specifically in the following manners:

[0057] Determine, according to the digital baseband signal and the matching characteristic parameter determination method, a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection;

[0058] The determination module determines multiple characteristic parameters in a characteristic parameter set used as a basis for frame detection according to the digital baseband signal and a matching characteristic parameter determination method, and the specific method includes:

[0059] Detecting a power parameter of the digital baseband signal, performing a power transition feature extraction operation on the power parameter, and obtaining a power transition feature included in a feature parameter set used as a basis for frame detection; and / or,

[0060] performing a first cross-correlation operation on the digital baseband signal and the first local reference sequence to obtain a first cross-correlation operation result, and performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection; and / or,

[0061] performing a first mutual correlation operation on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result, and performing a mutual correlation value jump feature extraction operation on the first mutual correlation operation result to obtain a mutual correlation value jump feature included in a feature parameter set used as a basis for frame detection; and / or,

[0062] A first mutual correlation operation is performed on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result; and a second mutual correlation operation is performed on the digital baseband signal and the second local reference sequence to obtain a second mutual correlation operation result; and a third mutual correlation operation is performed on the digital baseband signal and the third local reference sequence to obtain a third mutual correlation operation result; and an adjacent channel interference feature extraction operation is performed on the first mutual correlation operation result, the second mutual correlation operation result and the third mutual correlation operation result to obtain an adjacent channel interference feature included in a feature parameter set used as a basis for frame detection.

[0063] As an optional implementation, in the second aspect of the present invention, the second local reference sequence is obtained by forward shifting a first preset frequency component of a spectrum of the first local reference sequence; and / or,

[0064] The third local reference sequence is obtained by negatively shifting the frequency spectrum of the first local reference sequence by a second preset frequency component;

[0065] The first local reference sequence is determined according to a modulation method of the wireless signal frame.

[0066] As an optional implementation manner, in the second aspect of the present invention, the determination module detects the power parameter of the digital baseband signal, specifically in the following manner:

[0067] The power of the digital baseband signal in the determined target time period is calculated by sliding to obtain a power parameter, and the power parameter calculation formula is as follows:

[0068]

[0069] Wherein, P(n) represents the power parameter from the n-L+1th sampling point to the nth sampling point of the digital baseband signal within the target time period, L represents the total number of sampling points of the digital baseband signal within the target time period, and r(ni) represents the baseband input signal of the nith sampling point of the digital baseband signal within the target time period;

[0070] And, the determination module performs a power jump feature extraction operation on the power parameter to obtain a power jump feature included in a feature parameter set used as a basis for frame detection, specifically in the following manners:

[0071] Performing a smoothing filter operation on the power parameter to obtain a processed power parameter;

[0072] The difference between the power parameter and the processed power parameter is calculated to obtain a first difference; and the power jump feature included in the feature parameter set used as a basis for frame detection is determined according to the first difference.

[0073] As an optional implementation, in the second aspect of the present invention, the determination module performs a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection, and the specific method includes:

[0074] Calculating a modulus of the first cross-correlation operation result divided by a target result of the power parameter, and determining a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection according to the target result;

[0075] and / or,

[0076] The determination module performs a cross-correlation value jump feature extraction operation on the first cross-correlation operation result to obtain a cross-correlation value jump feature included in a feature parameter set used as a basis for frame detection, and the specific method includes:

[0077] Performing smoothing filtering on the modulus value of the first mutual correlation operation result to obtain a smoothing filtering result, and calculating the difference between the modulus value of the first mutual correlation operation result and the modulus value of the smoothing filtering result to obtain a second difference value; and determining the mutual correlation value jump feature included in the feature parameter set used as a basis for frame detection according to the second difference value;

[0078] and / or,

[0079] The determination module performs an adjacent channel interference feature extraction operation on the first mutual correlation operation result, the second mutual correlation operation result, and the third mutual correlation operation result to obtain adjacent channel interference features included in a feature parameter set used as a basis for frame detection, specifically in the following manner:

[0080] A first result is obtained by dividing the modulus of the first mutual correlation operation result by the second mutual correlation operation result, and a second result is obtained by dividing the modulus of the first mutual correlation operation result by the third mutual correlation operation result, and adjacent channel interference characteristics included in a feature parameter set used as a basis for frame detection are determined based on the maximum value of the first result and the second result.

[0081] As an optional implementation manner, in the second aspect of the present invention, the calculation formula corresponding to the first cross-correlation operation is as follows:

[0082]

[0083] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_0M(i) represents the ith value in the first local reference sequence, M represents the sequence length of the first local reference sequence, C_0M(n) represents the first cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate;

[0084] and / or,

[0085] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0086]

[0087] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_PM(i) represents the ith value in the second local reference sequence, M represents the sequence length of the second local reference sequence, C_PM(n) represents the second cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof;

[0088] and / or,

[0089] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0090]

[0091] Among them, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_NM(i) represents the i-th value in the third local reference sequence, M represents the sequence length of the third local reference sequence, C_NM(n) represents the third cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate.

[0092] The third aspect of the present invention discloses another target frame detection device based on multi-dimensional features, the device comprising:

[0093] A memory storing executable program code;

[0094] a processor coupled to the memory;

[0095] The processor calls the executable program code stored in the memory to execute part or all of the steps in the target frame detection method based on multi-dimensional features disclosed in the first aspect of the present invention.

[0096] The fourth aspect of the present invention discloses a computer-storable medium, which stores computer instructions. When the computer instructions are called, they are used to execute part or all of the steps in the target frame detection method based on multi-dimensional features disclosed in the first aspect of the present invention.

[0097] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0098] After converting the received wireless radio frequency signal into a digital baseband signal, the present invention determines a characteristic parameter set used as a basis for frame detection according to the digital baseband signal; and judges whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to multiple characteristic parameters in the characteristic parameter set to obtain a judgment result. It can be seen that the present invention can determine a characteristic parameter set according to the digital baseband signal, and judge whether the wireless signal frame is a target frame according to multiple characteristic parameters in the characteristic parameter set, which is conducive to improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0100] Figure 1 It is a flowchart of a target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention;

[0101] Figure 2 It is a schematic diagram of extracting power jump features of a target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention;

[0102] Figure 3 It is a schematic diagram of extracting cross-correlation peak features of a target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention;

[0103] Figure 4 It is a schematic diagram of extracting the cross-correlation value jump feature of the target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention;

[0104] Figure 5 It is a schematic diagram of extracting adjacent channel interference features of a target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention;

[0105] Figure 6 It is an overall framework diagram of the target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention;

[0106] Figure 7 It is a structural schematic diagram of a target frame detection device based on multi-dimensional features disclosed in an embodiment of the present invention;

[0107] Figure 8 It is a structural schematic diagram of another target frame detection device based on multi-dimensional features disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0108] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0109] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0110] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0111] The present invention discloses a target frame detection method and device based on multi-dimensional features, which can determine a feature parameter set according to a digital baseband signal, and judge whether a wireless signal frame is a target frame according to multiple feature parameters in the feature parameter set, which is conducive to improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network. The following are detailed descriptions.

[0112] Embodiment 1

[0113] See also Figure 1 , Figure 1 is a flow chart of a target frame detection method based on multi-dimensional features disclosed in an embodiment of the present invention. Figure 1The method shown can be applied to the application scenario of 802.11 frame detection based on multi-dimensional features, and can also be applied to other signal frame detection scenarios, such as signal frame detection scenarios using a fixed frame header format, which is not limited in the embodiment of the present invention. Figure 1 As shown, the target frame detection method based on multi-dimensional features may include the following operations:

[0114] 101. After converting the received wireless radio frequency signal into a digital baseband signal, determine a set of characteristic parameters used as a basis for frame detection according to the digital baseband signal;

[0115] In an embodiment of the present invention, the characteristic parameter set includes at least two characteristic parameters; wherein, if the target frame detected by the present invention is an 802.11 frame, the 802.11 frame adopts two modulation modes, OFDM and DSSS, and the OFDM frame header is composed of 10 short training symbols (STS) of 0.8us and 2 long training symbols (LTS) of 3.2us, wherein STS is used for frame detection, AGC, coarse frequency offset estimation and coarse timing estimation, etc.; the DSSS frame header is composed of a 128-bit SYNC field, each bit lasts for 1us, and is spread spectrum modulated by a complete Barker code sequence. 802.11 frame detection is achieved by detecting the above two frame headers.

[0116] 102. Determine, according to a plurality of characteristic parameters in the characteristic parameter set, whether a wireless signal frame carried by the wireless radio frequency signal is a target frame, and obtain a determination result.

[0117] It can be seen that the present invention can determine a characteristic parameter set used as a basis for frame detection according to the digital baseband signal after converting the received wireless radio frequency signal into a digital baseband signal; and judge whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to multiple characteristic parameters in the characteristic parameter set to obtain a judgment result. It can be seen that the present invention can determine a characteristic parameter set according to the digital baseband signal, and judge whether the wireless signal frame is a target frame according to multiple characteristic parameters in the characteristic parameter set, which is conducive to improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

[0118] In an optional embodiment, the characteristic parameter set includes at least two of a power jump characteristic, a cross-correlation peak characteristic, a cross-correlation value jump characteristic, and an adjacent channel interference characteristic;

[0119] Among them, in the above step 102, judging whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to the multiple characteristic parameters in the characteristic parameter set, and obtaining the judgment result may include:

[0120] For each characteristic parameter, determine whether the characteristic parameter satisfies a threshold condition corresponding to the characteristic parameter, and obtain a threshold condition determination result corresponding to the characteristic parameter;

[0121] According to the threshold condition judgment results corresponding to all characteristic parameters, the frame header validity judgment is performed on the wireless signal frame carried by the wireless radio frequency signal to obtain the frame header validity judgment result.

[0122] It can be seen that this optional embodiment can determine whether the characteristic parameter satisfies the threshold condition corresponding to it, obtain the threshold condition judgment result corresponding to the characteristic parameter, and perform frame header validity judgment on the wireless signal frame carried by the wireless RF signal based on the threshold condition judgment results corresponding to all characteristic parameters to obtain the frame header validity judgment result, which is beneficial to improve the determination accuracy of the threshold condition judgment result, thereby improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

[0123] In another optional embodiment, determining a set of characteristic parameters used as a basis for frame detection according to the digital baseband signal in the above step 101 may include:

[0124] Determine, according to the digital baseband signal and the matching characteristic parameter determination method, a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection;

[0125] The step of determining the plurality of characteristic parameters in the characteristic parameter set used as the basis for frame detection according to the digital baseband signal and the matching characteristic parameter determination method may include:

[0126] Detecting a power parameter of a digital baseband signal, performing a power transition feature extraction operation on the power parameter, and obtaining a power transition feature included in a feature parameter set used as a basis for frame detection; and / or,

[0127] performing a first cross-correlation operation on the digital baseband signal and the first local reference sequence to obtain a first cross-correlation operation result, and performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection; and / or,

[0128] performing a first mutual correlation operation on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result, and performing a mutual correlation value jump feature extraction operation on the first mutual correlation operation result to obtain a mutual correlation value jump feature included in a feature parameter set used as a basis for frame detection; and / or,

[0129] A first mutual correlation operation is performed on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result; and a second mutual correlation operation is performed on the digital baseband signal and the second local reference sequence to obtain a second mutual correlation operation result; and a third mutual correlation operation is performed on the digital baseband signal and the third local reference sequence to obtain a third mutual correlation operation result; and an adjacent channel interference feature extraction operation is performed on the first mutual correlation operation result, the second mutual correlation operation result and the third mutual correlation operation result to obtain an adjacent channel interference feature included in a feature parameter set used as a basis for frame detection.

[0130] In this optional embodiment, the cross-correlation operation is used to calculate the cross-correlation between the digital baseband signal and the local reference sequence; when a signal similar to the local reference sequence appears in the target channel, the cross-correlation value between the two is the largest; optionally, the cross-correlation operation is implemented by replacing it with a matched filter; further optionally, only the sign bit of the baseband input signal of the cross-correlation operation is taken, thereby simplifying the multiplication and accumulation calculation involved in the cross-correlation operation to an accumulation calculation, which can also achieve similar functions;

[0131] It can be seen that this optional embodiment can determine the power jump characteristics, cross-correlation peak characteristics, cross-correlation value jump characteristics and adjacent channel interference characteristics used as the basis for frame detection according to the digital baseband signal and the matching characteristic parameter determination method, which is beneficial to improve the accuracy of determining the characteristic parameters, thereby improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

[0132] In yet another optional embodiment, the second local reference sequence in the above step is obtained by forward shifting the frequency spectrum of the first local reference sequence by a first preset frequency component; and / or,

[0133] The third local reference sequence is obtained by negatively shifting the frequency spectrum of the first local reference sequence by a second preset frequency component;

[0134] The first local reference sequence is determined according to a modulation method of the wireless signal frame.

[0135] In this optional embodiment, the first local reference sequence, the second local reference sequence and the third local reference sequence may be pre-stored locally. When the OFDM frame header of the 802.11 frame is detected, the first local reference sequence is a short training sequence STS. When the DSSS frame header of the 802.11 frame is detected, the first local reference sequence is a Barker code sequence. The first preset frequency component may be 5 MHz, that is, the second local reference sequence may be obtained by shifting the first local reference sequence by +5 MHz, and the third local reference sequence may be obtained by shifting the first local reference sequence by -5 MHz.

[0136] It can be seen that this optional embodiment can determine the first local reference sequence according to the modulation mode of the wireless signal frame, and perform spectrum shifting based on the first local reference sequence to obtain the second local reference sequence and the third local reference sequence, which is beneficial to improve the determination accuracy of the first local reference sequence, the second local reference sequence and the third local reference sequence, and then improve the calculation accuracy of the first cross-correlation operation, the second cross-correlation operation and the third cross-correlation operation, thereby improving the determination accuracy of the adjacent channel interference characteristics, further improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the wireless network performance.

[0137] In yet another optional embodiment, detecting the power parameter of the digital baseband signal in the above step may include:

[0138] The power of the digital baseband signal in the determined target time period is calculated by sliding to obtain the power parameter. The power parameter calculation formula is as follows:

[0139]

[0140] Wherein, P(n) represents the power parameter of the digital baseband signal from the n-L+1th sampling point to the nth sampling point in the target time period, L represents the total number of sampling points of the digital baseband signal in the target time period, r(ni) represents the baseband input signal of the nith sampling point of the digital baseband signal in the target time period; when detecting the OFDM frame header of the 802.11 frame, the target time period T=N*0.8us, when detecting the DSSS frame header of the 802.11 frame, the target time period T=N*1us, and N can be an integer between 1 and 10;

[0141] And, in the above step, performing a power transition feature extraction operation on the power parameter to obtain a power transition feature included in a feature parameter set used as a basis for frame detection may include:

[0142] Performing a smoothing filter operation on the power parameter to obtain a processed power parameter;

[0143] The difference between the power parameter and the processed power parameter is calculated to obtain a first difference; and the power jump feature included in the feature parameter set used as a basis for frame detection is determined according to the first difference.

[0144] In this optional embodiment, the principle of extracting the power jump feature is as follows: Figure 2 shown.

[0145] It can be seen that this optional embodiment can slidingly calculate the power of the digital baseband signal within the determined target time period to obtain the power parameter, which is beneficial to improving the accuracy of determining the power parameter; at the same time, it can also perform a smoothing filtering operation on the power parameter to obtain a processed power parameter, calculate the difference between the power parameter and the processed power parameter to obtain a first difference, and determine the power jump feature included in the feature parameter set used as the basis for frame detection based on the first difference, which is beneficial to improving the accuracy of determining the power jump feature, and then improving the accuracy of judging whether the wireless signal frame is a target frame through the power jump feature, reducing the probability of false detection and missed detection of the target frame, thereby improving the performance of the wireless network.

[0146] In yet another optional embodiment, the above step of performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection may include:

[0147] Calculate the modulus of the first cross-correlation operation result divided by the target result of the power parameter, and determine the cross-correlation peak feature included in the feature parameter set used as a basis for frame detection according to the target result;

[0148] and / or,

[0149] In the above step, performing a cross-correlation value jump feature extraction operation on the first cross-correlation operation result to obtain a cross-correlation value jump feature included in a feature parameter set used as a basis for frame detection may include:

[0150] Performing smoothing filtering on the modulus value of the first mutual correlation operation result to obtain a smoothing filtering result, and calculating the difference between the modulus value of the first mutual correlation operation result and the modulus value of the smoothing filtering result to obtain a second difference value; and determining the mutual correlation value jump feature included in the feature parameter set used as a basis for frame detection according to the second difference value;

[0151] and / or,

[0152] In the above step, performing the adjacent channel interference feature extraction operation on the first mutual correlation operation result, the second mutual correlation operation result, and the third mutual correlation operation result to obtain the adjacent channel interference feature included in the feature parameter set used as the basis for frame detection may include:

[0153] A first result is obtained by dividing the modulus value of the first mutual correlation operation result by the second mutual correlation operation result, and a second result is obtained by dividing the modulus value of the first mutual correlation operation result by the third mutual correlation operation result, and the adjacent channel interference characteristics included in the feature parameter set used as the basis for frame detection are determined based on the maximum value of the first result and the second result.

[0154] In this optional embodiment, the principle of extracting the cross-correlation peak feature is as follows: Figure 3As shown in the figure, the extraction principle of the cross-correlation value jump feature is as follows Figure 4 As shown in the figure, the principle of extracting adjacent channel interference features is as follows Figure 5 shown.

[0155] It can be seen that this optional embodiment can further determine the calculation method of the mutual correlation peak characteristics, mutual correlation value jump characteristics and adjacent channel interference characteristics included in the characteristic parameter set, which is beneficial to improve the accuracy of determining the mutual correlation peak characteristics, mutual correlation value jump characteristics and adjacent channel interference characteristics, and then improve the accuracy of judging whether the wireless signal frame is the target frame through the characteristic parameter set, reduce the probability of false detection and missed detection of the target frame, and thus improve the performance of the wireless network.

[0156] In yet another optional embodiment, the calculation formula corresponding to the first cross-correlation operation in the above steps is as follows:

[0157]

[0158] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_0M(i) represents the i-th value in the first local reference sequence, M represents the sequence length of the first local reference sequence, C_0M(n) represents the first cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof;

[0159] and / or,

[0160] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0161]

[0162] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_PM(i) represents the ith value in the second local reference sequence, M represents the sequence length of the second local reference sequence, C_PM(n) represents the second cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof;

[0163] and / or,

[0164] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0165]

[0166] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_NM(i) represents the i-th value in the third local reference sequence, M represents the sequence length of the third local reference sequence, C_NM(n) represents the third cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate.

[0167] It can be seen that this optional embodiment can further determine the calculation formulas corresponding to the first mutual correlation operation, the second mutual correlation operation and the third mutual correlation operation, which is beneficial to improve the calculation accuracy of the first mutual correlation operation results, the second mutual correlation operation results and the third mutual correlation operation results, and then improve the accuracy of determining the adjacent channel interference characteristics, thereby improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and improving the performance of the wireless network.

[0168] In yet another optional embodiment, for each characteristic parameter in the above steps, determining whether the characteristic parameter satisfies a threshold condition corresponding thereto and obtaining a threshold condition determination result corresponding to the characteristic parameter may include:

[0169] Determine whether the power jump feature satisfies the power jump feature threshold condition corresponding thereto, and obtain a power jump feature threshold determination result corresponding to the power jump feature; and / or,

[0170] Determine whether the cross-correlation peak feature satisfies the cross-correlation peak feature threshold condition corresponding thereto, and obtain the cross-correlation peak feature threshold determination result corresponding to the cross-correlation peak feature; and / or,

[0171] Determine whether the mutual correlation value jump feature satisfies the mutual correlation value jump feature threshold condition corresponding thereto, and obtain the mutual correlation value jump feature threshold judgment result corresponding to the mutual correlation value jump feature; and / or,

[0172] Determine whether the adjacent channel interference feature satisfies the adjacent channel interference feature threshold condition corresponding thereto, and obtain the adjacent channel interference feature threshold determination result corresponding to the adjacent channel interference feature;

[0173] And, according to the threshold condition judgment results corresponding to all characteristic parameters, performing frame header validity judgment on the wireless signal frame carried by the wireless radio frequency signal to obtain the frame header validity judgment result may include:

[0174] The frame header validity judgment result is determined based on the power jump feature threshold judgment result corresponding to the power jump feature, and / or the mutual correlation peak feature threshold judgment result corresponding to the mutual correlation peak feature, and / or the mutual correlation value jump feature threshold judgment result corresponding to the mutual correlation value jump feature, and / or the adjacent channel interference feature threshold judgment result corresponding to the adjacent channel interference feature.

[0175] In this optional embodiment, when the characteristic parameter set includes power jump characteristics, cross-correlation peak characteristics, cross-correlation value jump characteristics and adjacent channel interference characteristics, the overall framework diagram of this embodiment can be as follows: Figure 6 shown.

[0176] It can be seen that this optional embodiment can determine whether the power jump characteristics, cross-correlation peak characteristics, cross-correlation value jump characteristics and adjacent channel interference characteristics respectively meet the corresponding threshold conditions, and obtain the threshold condition judgment result corresponding to each characteristic parameter, and obtain the frame header validity judgment result based on the threshold condition judgment result corresponding to each characteristic parameter, which is beneficial to improve the determination accuracy of the frame header validity judgment result, and then improve the detection accuracy of the target frame, reduce the probability of false detection and missed detection of the target frame, and thus improve the wireless network performance.

[0177] Embodiment 2

[0178] See also Figure 7 , Figure 7 is a schematic diagram of the structure of a target frame detection device based on multi-dimensional features disclosed in an embodiment of the present invention. Figure 7 The device shown can be applied to the application scenario of 802.11 frame detection based on multi-dimensional features, and can also be applied to other signal frame detection scenarios, such as signal frame detection scenarios using a fixed frame header format, which is not limited in the embodiment of the present invention. Figure 7 As shown, the target frame detection device based on multi-dimensional features may include:

[0179] The determination module 201 is used to determine a characteristic parameter set used as a basis for frame detection according to the digital baseband signal after converting the received wireless radio frequency signal into a digital baseband signal; the characteristic parameter set includes at least two characteristic parameters;

[0180] The judgment module 202 is used to judge whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to multiple characteristic parameters in the characteristic parameter set, and obtain a judgment result.

[0181] In the embodiment of the present invention, if the target frame detected by the present invention is an 802.11 frame, the 802.11 frame adopts two modulation modes, OFDM and DSSS, and the OFDM frame header is composed of 10 short training symbols (STS) of 0.8us and 2 long training symbols (LTS) of 3.2us, wherein STS is used for frame detection, AGC, coarse frequency offset estimation and coarse timing estimation, etc.; the DSSS frame header is composed of a 128-bit SYNC field, each bit lasts for 1us, and is spread spectrum modulated by a complete Barker code sequence. 802.11 frame detection is achieved by detecting the above two frame headers.

[0182] It can be seen that the device described in the embodiment of the present invention can determine a characteristic parameter set used as a basis for frame detection according to the digital baseband signal after converting the received wireless radio frequency signal into a digital baseband signal; and judge whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to multiple characteristic parameters in the characteristic parameter set to obtain a judgment result. It can be seen that the present invention can determine a characteristic parameter set according to the digital baseband signal and judge whether the wireless signal frame is a target frame according to multiple characteristic parameters in the characteristic parameter set, which is conducive to improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

[0183] In an optional embodiment, the characteristic parameter set includes at least two of a power jump characteristic, a cross-correlation peak characteristic, a cross-correlation value jump characteristic, and an adjacent channel interference characteristic;

[0184] The judgment module 202 judges whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to the multiple characteristic parameters in the characteristic parameter set, and obtains the judgment result, and the specific method includes:

[0185] For each characteristic parameter, determine whether the characteristic parameter satisfies a threshold condition corresponding to the characteristic parameter, and obtain a threshold condition determination result corresponding to the characteristic parameter;

[0186] According to the threshold condition judgment results corresponding to all characteristic parameters, the frame header validity judgment is performed on the wireless signal frame carried by the wireless radio frequency signal to obtain the frame header validity judgment result.

[0187] It can be seen that the device described in the embodiment of the present invention can determine whether the characteristic parameter meets the threshold condition corresponding to the characteristic parameter, obtain the threshold condition judgment result corresponding to the characteristic parameter, and perform frame header validity judgment on the wireless signal frame carried by the wireless radio frequency signal based on the threshold condition judgment results corresponding to all characteristic parameters to obtain the frame header validity judgment result; it is beneficial to improve the determination accuracy of the threshold condition judgment result, thereby improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

[0188] In another optional embodiment, the determination module 201 determines a set of characteristic parameters used as a basis for frame detection according to the digital baseband signal, specifically in the following manner:

[0189] Determine, according to the digital baseband signal and the matching characteristic parameter determination method, a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection;

[0190] The determination module 201 determines multiple characteristic parameters in a characteristic parameter set used as a basis for frame detection according to the digital baseband signal and a matching characteristic parameter determination method, and the specific method includes:

[0191] Detecting a power parameter of a digital baseband signal, performing a power transition feature extraction operation on the power parameter, and obtaining a power transition feature included in a feature parameter set used as a basis for frame detection; and / or,

[0192] performing a first cross-correlation operation on the digital baseband signal and the first local reference sequence to obtain a first cross-correlation operation result, and performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection; and / or,

[0193] performing a first mutual correlation operation on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result, and performing a mutual correlation value jump feature extraction operation on the first mutual correlation operation result to obtain a mutual correlation value jump feature included in a feature parameter set used as a basis for frame detection; and / or,

[0194] A first mutual correlation operation is performed on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result; and a second mutual correlation operation is performed on the digital baseband signal and the second local reference sequence to obtain a second mutual correlation operation result; and a third mutual correlation operation is performed on the digital baseband signal and the third local reference sequence to obtain a third mutual correlation operation result; and an adjacent channel interference feature extraction operation is performed on the first mutual correlation operation result, the second mutual correlation operation result and the third mutual correlation operation result to obtain an adjacent channel interference feature included in a feature parameter set used as a basis for frame detection.

[0195] It can be seen that the device described in the embodiment of the present invention can determine the power jump characteristics, cross-correlation peak characteristics, cross-correlation value jump characteristics and adjacent channel interference characteristics used as the basis for frame detection according to the digital baseband signal and the matching characteristic parameter determination method, which is beneficial to improve the accuracy of determining the characteristic parameters, thereby improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the performance of the wireless network.

[0196] In yet another optional embodiment, the second local reference sequence is obtained by forward shifting the frequency spectrum of the first local reference sequence by a first preset frequency component; and / or,

[0197] The third local reference sequence is obtained by negatively shifting the frequency spectrum of the first local reference sequence by a second preset frequency component;

[0198] The first local reference sequence is determined according to a modulation method of the wireless signal frame.

[0199] In this optional embodiment, the first local reference sequence, the second local reference sequence and the third local reference sequence can be pre-stored locally. When the OFDM frame header is detected, the first local reference sequence is a short training sequence STS, and when the DSSS frame header is detected, the first local reference sequence is a Barker code sequence; the first preset frequency component can be 5MHz; that is, the second local reference sequence can be obtained by shifting the first local reference sequence by +5MHz; the third local reference sequence can be obtained by shifting the first local reference sequence by -5MHz;

[0200] It can be seen that the device described in the embodiment of the present invention can determine the first local reference sequence according to the modulation method of the wireless signal frame, and perform spectrum shifting based on the first local reference sequence to obtain the second local reference sequence and the third local reference sequence, which is beneficial to improving the determination accuracy of the first local reference sequence, the second local reference sequence and the third local reference sequence, and then improving the calculation accuracy of the first cross-correlation operation, the second cross-correlation operation and the third cross-correlation operation, thereby improving the determination accuracy of the adjacent channel interference characteristics, further improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and thus improving the wireless network performance.

[0201] As an optional implementation, in the second aspect of the present invention, the determination module 201 detects the power parameter of the digital baseband signal, specifically in the following manner:

[0202] The power of the digital baseband signal in the determined target time period is calculated by sliding to obtain the power parameter. The power parameter calculation formula is as follows:

[0203]

[0204] Wherein, P(n) represents the power parameter of the digital baseband signal from the n-L+1th sampling point to the nth sampling point in the target time period, L represents the total number of sampling points of the digital baseband signal in the target time period, r(ni) represents the baseband input signal of the nith sampling point of the digital baseband signal in the target time period; when detecting the OFDM frame header of the 802.11 frame, the target time period T=N*0.8us, when detecting the DSSS frame header of the 802.11 frame, the target time period T=N*1us, and N can be an integer between 1 and 10;

[0205] And, the determination module 201 performs a power jump feature extraction operation on the power parameter to obtain a power jump feature included in a feature parameter set used as a basis for frame detection, specifically in the following manners:

[0206] Performing a smoothing filter operation on the power parameter to obtain a processed power parameter;

[0207] The difference between the power parameter and the processed power parameter is calculated to obtain a first difference; and the power jump feature included in the feature parameter set used as a basis for frame detection is determined according to the first difference.

[0208] It can be seen that the device described in the embodiment of the present invention can slidingly calculate the power of the digital baseband signal within the determined target time period to obtain the power parameter, which is beneficial to improving the accuracy of determining the power parameter; at the same time, it can also perform a smoothing filtering operation on the power parameter to obtain a processed power parameter, calculate the difference between the power parameter and the processed power parameter to obtain a first difference, and determine the power jump feature included in the feature parameter set used as the basis for frame detection based on the first difference, which is beneficial to improving the accuracy of determining the power jump feature, and then improving the accuracy of judging whether the wireless signal frame is a target frame through the power jump feature, reducing the probability of false detection and missed detection of the target frame, thereby improving the performance of the wireless network.

[0209] In yet another optional embodiment, the determination module 201 performs a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection, specifically in the following manner:

[0210] Calculate the modulus of the first cross-correlation operation result divided by the target result of the power parameter, and determine the cross-correlation peak feature included in the feature parameter set used as a basis for frame detection according to the target result;

[0211] and / or,

[0212] The determination module 201 performs a cross-correlation value jump feature extraction operation on the first cross-correlation operation result to obtain a cross-correlation value jump feature included in a feature parameter set used as a basis for frame detection, and the specific method includes:

[0213] Performing smoothing filtering on the modulus value of the first mutual correlation operation result to obtain a smoothing filtering result, and calculating the difference between the modulus value of the first mutual correlation operation result and the modulus value of the smoothing filtering result to obtain a second difference value; and determining the mutual correlation value jump feature included in the feature parameter set used as a basis for frame detection according to the second difference value;

[0214] and / or,

[0215] The determination module 201 performs an adjacent channel interference feature extraction operation on the first cross-correlation operation result, the second cross-correlation operation result, and the third cross-correlation operation result to obtain adjacent channel interference features included in a feature parameter set used as a basis for frame detection, specifically in the following manners:

[0216] A first result is obtained by dividing the modulus value of the first mutual correlation operation result by the second mutual correlation operation result, and a second result is obtained by dividing the modulus value of the first mutual correlation operation result by the third mutual correlation operation result, and the adjacent channel interference characteristics included in the feature parameter set used as the basis for frame detection are determined based on the maximum value of the first result and the second result.

[0217] It can be seen that the device described in the embodiment of the present invention can further determine the calculation method of the mutual correlation peak characteristics, mutual correlation value jump characteristics and adjacent channel interference characteristics included in the characteristic parameter set, which is beneficial to improve the accuracy of determining the mutual correlation peak characteristics, mutual correlation value jump characteristics and adjacent channel interference characteristics, and then improve the accuracy of judging whether the wireless signal frame is the target frame through the characteristic parameter set, reduce the probability of false detection and missed detection of the target frame, and thus improve the performance of the wireless network.

[0218] In yet another optional embodiment, the calculation formula corresponding to the first cross-correlation operation is as follows:

[0219]

[0220] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_0M(i) represents the i-th value in the first local reference sequence, M represents the sequence length of the first local reference sequence, C_0M(n) represents the first cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof;

[0221] and / or,

[0222] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0223]

[0224] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_PM(i) represents the ith value in the second local reference sequence, M represents the sequence length of the second local reference sequence, C_PM(n) represents the second cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof;

[0225] and / or,

[0226] The calculation formula corresponding to the second cross-correlation operation is as follows:

[0227]

[0228] Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_NM(i) represents the i-th value in the third local reference sequence, M represents the sequence length of the third local reference sequence, C_NM(n) represents the third cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate.

[0229] It can be seen that the device described in the embodiment of the present invention can further determine the calculation formulas corresponding to the first mutual correlation operation, the second mutual correlation operation and the third mutual correlation operation, which is beneficial to improve the calculation accuracy of the first mutual correlation operation result, the second mutual correlation operation result and the third mutual correlation operation result, and then improve the accuracy of determining the adjacent channel interference characteristics, thereby improving the detection accuracy of the target frame, reducing the probability of false detection and missed detection of the target frame, and improving the performance of the wireless network.

[0230] Embodiment 3

[0231] See also Figure 8 , Figure 8 is a schematic diagram of the structure of another target frame detection device based on multi-dimensional features disclosed in an embodiment of the present invention. Figure 8 The described device can be applied in an application server. Figure 8 As shown, the device may include:

[0232] A memory 301 storing executable program codes;

[0233] a processor 302 coupled to the memory 301;

[0234] The processor 302 calls the executable program code stored in the memory 301 to execute the steps in the target frame detection method based on multi-dimensional features described in the first embodiment of the present invention.

[0235] Embodiment 4

[0236] An embodiment of the present invention discloses a computer storable medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps in the target frame detection method based on multi-dimensional features described in the first embodiment of the present invention.

[0237] Embodiment 5

[0238] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the target frame detection method based on multi-dimensional features described in Embodiment 1 of the present invention.

[0239] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0240] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0241] Finally, it should be noted that the target frame detection method and device based on multi-dimensional features disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, which are only used to illustrate the technical scheme of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical schemes described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical schemes from the spirit and scope of the technical schemes of the embodiments of the present invention.

Claims

1. A target frame detection method based on multi-dimensional features, characterized in that: The method comprises: After converting the received wireless radio frequency signal into a digital baseband signal, determining a characteristic parameter set used as a basis for frame detection according to the digital baseband signal; the characteristic parameter set includes at least two characteristic parameters; According to the plurality of characteristic parameters in the characteristic parameter set, it is determined whether the wireless signal frame carried by the wireless radio frequency signal is a target frame to obtain a determination result.

2. The target frame detection method based on multi-dimensional features according to claim 1, characterized in that: The characteristic parameter set includes at least two of a power jump characteristic, a cross-correlation peak characteristic, a cross-correlation value jump characteristic, and an adjacent channel interference characteristic; Wherein, judging whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to the plurality of characteristic parameters in the characteristic parameter set, and obtaining a judgment result includes: For each of the characteristic parameters, determining whether the characteristic parameter satisfies a threshold condition corresponding to the characteristic parameter, and obtaining a threshold condition determination result corresponding to the characteristic parameter; According to the threshold condition judgment results corresponding to all the characteristic parameters, a frame header validity judgment is performed on the wireless signal frame carried by the wireless radio frequency signal to obtain a frame header validity judgment result.

3. The target frame detection method based on multi-dimensional features according to claim 2, characterized in that: The step of determining a set of characteristic parameters used as a basis for frame detection according to the digital baseband signal comprises: Determine, according to the digital baseband signal and the matching characteristic parameter determination method, a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection; Wherein, the determining of a plurality of characteristic parameters in a characteristic parameter set used as a basis for frame detection according to the digital baseband signal and a matching characteristic parameter determination method includes: Detecting a power parameter of the digital baseband signal, performing a power transition feature extraction operation on the power parameter, and obtaining a power transition feature included in a feature parameter set used as a basis for frame detection; and / or, performing a first cross-correlation operation on the digital baseband signal and the first local reference sequence to obtain a first cross-correlation operation result, and performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection; and / or, performing a first mutual correlation operation on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result, and performing a mutual correlation value jump feature extraction operation on the first mutual correlation operation result to obtain a mutual correlation value jump feature included in a feature parameter set used as a basis for frame detection; and / or, A first mutual correlation operation is performed on the digital baseband signal and the first local reference sequence to obtain a first mutual correlation operation result; and a second mutual correlation operation is performed on the digital baseband signal and the second local reference sequence to obtain a second mutual correlation operation result; and a third mutual correlation operation is performed on the digital baseband signal and the third local reference sequence to obtain a third mutual correlation operation result; and an adjacent channel interference feature extraction operation is performed on the first mutual correlation operation result, the second mutual correlation operation result and the third mutual correlation operation result to obtain an adjacent channel interference feature included in a feature parameter set used as a basis for frame detection.

4. The target frame detection method based on multi-dimensional features according to claim 3 is characterized in that: The second local reference sequence is obtained by forward shifting a first preset frequency component of the spectrum of the first local reference sequence; and / or, The third local reference sequence is obtained by negatively shifting the frequency spectrum of the first local reference sequence by a second preset frequency component; The first local reference sequence is determined according to a modulation method of the wireless signal frame.

5. The target frame detection method based on multi-dimensional features according to claim 3 is characterized in that: The detecting the power parameter of the digital baseband signal comprises: The power of the digital baseband signal in the determined target time period is calculated by sliding to obtain a power parameter, and the power parameter calculation formula is as follows: Wherein, P(n) represents the power parameter from the n-L+1th sampling point to the nth sampling point of the digital baseband signal within the target time period, L represents the total number of sampling points of the digital baseband signal within the target time period, and r(ni) represents the baseband input signal of the nith sampling point of the digital baseband signal within the target time period; And, performing a power transition feature extraction operation on the power parameter to obtain a power transition feature included in a feature parameter set used as a basis for frame detection includes: Performing a smoothing filter operation on the power parameter to obtain a processed power parameter; The difference between the power parameter and the processed power parameter is calculated to obtain a first difference; and the power jump feature included in the feature parameter set used as a basis for frame detection is determined according to the first difference.

6. The target frame detection method based on multi-dimensional features according to claim 5, characterized in that: The performing a cross-correlation peak feature extraction operation on the first cross-correlation operation result and the power parameter to obtain a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection includes: Calculating a modulus of the first cross-correlation operation result divided by a target result of the power parameter, and determining a cross-correlation peak feature included in a feature parameter set used as a basis for frame detection according to the target result; and / or, The performing of a mutual correlation value jump feature extraction operation on the first mutual correlation operation result to obtain a mutual correlation value jump feature included in a feature parameter set used as a basis for frame detection includes: Performing smoothing filtering on the modulus value of the first mutual correlation operation result to obtain a smoothing filtering result, and calculating the difference between the modulus value of the first mutual correlation operation result and the modulus value of the smoothing filtering result to obtain a second difference value; and determining the mutual correlation value jump feature included in the feature parameter set used as a basis for frame detection according to the second difference value; and / or, The performing of the adjacent channel interference feature extraction operation on the first mutual correlation operation result, the second mutual correlation operation result, and the third mutual correlation operation result to obtain the adjacent channel interference feature included in the feature parameter set used as a basis for frame detection includes: A first result is obtained by dividing the modulus of the first mutual correlation operation result by the second mutual correlation operation result, and a second result is obtained by dividing the modulus of the first mutual correlation operation result by the third mutual correlation operation result, and adjacent channel interference characteristics included in a feature parameter set used as a basis for frame detection are determined based on the maximum value of the first result and the second result.

7. The target frame detection method based on multi-dimensional features according to claim 6, characterized in that: The calculation formula corresponding to the first cross-correlation operation is as follows: Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_0M(i) represents the ith value in the first local reference sequence, M represents the sequence length of the first local reference sequence, C_0M(n) represents the first cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate; and / or, The calculation formula corresponding to the second cross-correlation operation is as follows: Wherein, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_PM(i) represents the ith value in the second local reference sequence, M represents the sequence length of the second local reference sequence, C_PM(n) represents the second cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking the conjugate thereof; and / or, The calculation formula corresponding to the second cross-correlation operation is as follows: Among them, r(ni) represents the baseband input signal of the ni-th sampling point of the digital baseband signal, LocSeq_NM(i) represents the i-th value in the third local reference sequence, M represents the sequence length of the third local reference sequence, C_NM(n) represents the third cross-correlation operation result from the n-M+1-th sampling point to the n-th sampling point of the digital baseband signal, and * represents taking its conjugate.

8. A target frame detection device based on multi-dimensional features, characterized in that: The device comprises: A determination module, configured to determine a characteristic parameter set used as a basis for frame detection according to the digital baseband signal after converting the received wireless radio frequency signal into a digital baseband signal; the characteristic parameter set includes at least two characteristic parameters; The judgment module is used to judge whether the wireless signal frame carried by the wireless radio frequency signal is a target frame according to a plurality of the characteristic parameters in the characteristic parameter set, and obtain a judgment result.

9. A target frame detection device based on multi-dimensional features, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the target frame detection method based on multi-dimensional features as described in any one of claims 1-7.

10. A computer storable medium, characterized in that: The computer storage medium stores computer instructions, which, when called, are used to execute the target frame detection method based on multi-dimensional features as described in any one of claims 1-7.

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