Multi-node wireless sensing network topology dynamic adjustment method

Abstract

The invention discloses a multi-node wireless sensing network topology dynamic adjustment method, and particularly relates to the field of detection equipment. Comprising the following steps: transmitting detection data packets through a transmitting end, and respectively obtaining the detection data packets received by each receiving end; determining the signal receiving strength of the received detection data packet, and generating a signal receiving strength sequence of each receiving end by using the signal receiving strength; and determining the fluctuation degree of the signal receiving strength sequence of each receiving end, and adjusting the wireless sensing network topology according to the similarity degree of the fluctuation degrees. According to the method, the potential sensing link in the multi-node sensing network can be explored, so that the richness of sensing data is greatly improved, and wireless sensing application can better adapt to a dynamically changing actual sensing scene and can adapt to a complex sensing environment.

Description

Technical Field

[0001] The present application relates to the field of detection equipment, and in particular to a method for dynamically adjusting the topology of a multi-node wireless sensing network. Background Art

[0002] With the continuous development of wireless communication technology, ubiquitous radio waves have become an important carrier of communication in human society. As an important wireless LAN communication technology, WIFI communication technology has the advantages of high portability, strong scalability and low cost. In addition to wireless communication, wireless sensing technology using electromagnetic waves as the sensing medium has developed rapidly in recent years. Compared with the use of dedicated sensors, wireless sensing technology has the advantages of low intrusion and strong ubiquity. In the current field of wireless sensing research, WIFI sensing technology has a wide range of research and application scenarios due to its low equipment price and wide distribution.

[0003] As research progresses, WIFI sensing technology is also facing a series of challenges: since WIFI devices are often used with omnidirectional antennas and have low signal bandwidth, their sensing effect and accuracy are poor, and due to the influence of noise and indoor multipath effects, WIFI sensing technology has poor stability in different sensing environments. In order to reduce the impact of the above challenges, a sensing network can be built by adding heterogeneous WIFI sensing nodes for collaborative sensing. By exploring dynamically collaborative heterogeneous wireless sensing technologies, the applicability of current wireless sensing research can be improved in increasingly complex sensing environments, laying the foundation for the implementation of wireless sensing technology.

[0004] However, the current research work on multi-device wireless perception faces the following challenges: most of the work is aimed at perception tasks in specific scenarios, and the location of the perception devices is often fixed, the participation is fixed, the hardware information is isomorphic, and the structure of the overall perception network is fixed. It cannot adapt well to the complex perception conditions of dynamic changes in device location and participation in actual scenarios, heterogeneous hardware, and dynamic changes in the perception network. Wireless perception platform work is needed to fill the blank area between theory and application. However, the current wireless perception platform has a long history of development, supports relatively single devices, has a cumbersome workflow, and does not consider the dynamic changes of nodes, so it is difficult to adapt to complex perception environments. Summary of the invention

[0005] The main purpose of the present application is to provide a method for dynamically adjusting the topology of a multi-node wireless sensing network, aiming to solve the problem that existing multi-device wireless sensing devices are difficult to adapt to complex sensing environments.

[0006] To achieve the above-mentioned purpose, the present application provides a method for dynamically adjusting the topology of a multi-node wireless sensing network. The wireless sensing network topology includes a transmitting end and at least two receiving ends. The method includes: transmitting a detection data packet through the transmitting end, and obtaining the detection data packets received by each receiving end respectively; determining the signal reception strength of the received detection data packet, and using the signal reception strength to generate a signal reception strength sequence for each receiving end; setting a sliding window to determine the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window; using the frequency value corresponding to the RSSI element, generating a frequency vector for each sliding window; determining the degree of fluctuation between the frequency vectors of all two adjacent sliding windows in each receiving end, and combining all the fluctuation degrees to obtain the fluctuation sequence of each receiving end; determining the degree of similarity between the fluctuation sequence of each receiving end and the fluctuation sequence of other receiving ends; and adjusting the transmitting end and the receiving end according to the degree of similarity.

[0007] Optionally, the RSSI element includes multiple RSSI values, and the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window is determined. The frequency vector of each sliding window is generated using the frequency value corresponding to the RSSI element, including: determining the frequency value of each RSSI value appearing in the signal reception strength sequence of each sliding window, combining the frequency values ​​corresponding to all RSSI values ​​in each sliding window, and obtaining the frequency vector of each sliding window.

[0008] Optionally, the RSSI element is represented as: ,in, is the maximum possible RSSI value, is the RSSI value.

[0009] Optionally, the degree of similarity is determined by the Euclidean distance between two fluctuation series.

[0010] Optionally, the transmitting end and the receiving end are adjusted according to the degree of similarity, including: when the Euclidean distance between two fluctuation sequences is greater than a preset threshold, the transmitting end is adjusted to the receiving end, and the peak value of each fluctuation sequence is obtained, and the receiving end with the largest peak value is adjusted to the new transmitting end.

[0011] Optionally, the degree of fluctuation is determined by the Euclidean distance between the frequency vectors of two sliding windows.

[0012] Optionally, the formula for the fluctuation sequence at each receiving end is as follows:

[0013] In the formula, is the ith fluctuation sequence, is the number of sliding windows, is the degree of fluctuation, and is the frequency vector of two adjacent sliding windows.

[0014] Optionally, before determining the degree of similarity between each fluctuation sequence and other fluctuation sequences, the method also includes: smoothing each fluctuation sequence and making the length of each fluctuation sequence the same through an interpolation resampling method; and normalizing the fluctuation sequence after interpolation resampling to a preset interval.

[0015] Optionally, the preset interval is 0-1.

[0016] To achieve the above-mentioned purpose, the present application also provides a multi-node wireless sensing network topology dynamic adjustment device, the wireless sensing network topology includes a transmitting end and at least two receiving ends, and the device includes: an acquisition module, which is used to transmit a detection data packet through the transmitting end and obtain the detection data packet received by each receiving end respectively; a signal reception strength sequence generation module, which determines the signal reception strength of the received detection data, and uses the signal reception strength to generate a signal reception strength sequence for each receiving end; a frequency vector generation module, which sets a sliding window and determines the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window; uses the frequency value corresponding to the RSSI element to generate a frequency vector for each sliding window; a fluctuation sequence generation module, which determines the degree of fluctuation between the frequency vectors of all two adjacent sliding windows in each receiving end, and combines all the fluctuation degrees to obtain the fluctuation sequence of each receiving end; an adjustment module, which determines the degree of similarity between the fluctuation sequence of each receiving end and the fluctuation sequence of other receiving ends, and adjusts the transmitting end and the receiving end according to the degree of similarity.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The method for dynamically adjusting the topology of a multi-node wireless sensing network of the present invention can infer the relative position of a human body in a sensing network by calculating the similarity of RSSI signal fluctuations of different terminals, thereby dynamically adjusting the topological structure of the network; by switching between a transmitting end and a receiving end, it can explore potential sensing links in a multi-node sensing network, thereby greatly improving the richness of sensing data, so that wireless sensing applications can better adapt to dynamically changing actual sensing scenarios and complex sensing environments; compared with the traditional variance-based signal fluctuation degree calculation method or the smoothing filtering-based outlier removal method, by vectorizing the signal reception strength of the receiving end and determining the fluctuation of the vector by the Euclidean distance, vectorized fluctuations are realized, and stable and reliable fluctuation feature calculation can be realized while retaining all RSSI information, without causing drastic changes in numerical values ​​and affecting subsequent calculations. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1This is a structural diagram of a wireless sensing network topology in a multi-node wireless sensing network topology dynamic adjustment method of the present application; Figure 2 A flowchart of a method for dynamically adjusting topology of a multi-node wireless sensing network is provided for this application; Figure 3 This is a structural diagram of the wireless sensing network topology in Example 1 of the present application; Figure 4 This is a schematic diagram of data processing at different stages obtained in Example 1 of the present application; Figure 5 This is a diagram illustrating the principle of different signal characteristics caused by different Fresnel zones in a multi-node wireless sensing network topology dynamic adjustment method of this application; Figure 6 This is a diagram of a wireless sensing network topology adjustment process in a multi-node wireless sensing network topology dynamic adjustment method of the present application.

[0019] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] The first embodiment of the present invention provides a method for dynamically adjusting the topology of a multi-node wireless sensing network. Figure 1 As shown, the wireless sensing network topology includes a transmitter and at least two receivers, and the transmitter and the receiver are equipped with a hardware network card device and a software driver that can read the sensing data; Figure 2 As shown, the specific steps include: Step S1, transmitting a detection data packet through the transmitting end, respectively obtaining the detection data packet received by each receiving end; determining the signal receiving strength (RSSI) of the received detection data packet, and using the signal receiving strength, generating a signal receiving strength sequence of each receiving end; In this embodiment, the signal reception strengths of all the detection data packets received by each receiving end are calculated, and the signal reception strengths of all the detection data packets are combined to obtain a signal reception strength sequence S of each receiving end.

[0022] Step S2, setting a sliding window, determining the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window; using the frequency value corresponding to the RSSI element, generating a frequency vector for each sliding window; Exemplarily, the RSSI element includes multiple RSSI values, and the RSSI element is represented as:

[0023] In the formula, is the maximum possible RSSI value.

[0024] Specifically, set the length to The sliding window is set and the step length is , and continuously step the sliding window in the signal reception strength sequence of each receiving end. The signal reception strength sequence S in each sliding window is:

[0025] In the formula, is the length of the sliding window.

[0026] Determine the frequency value of each RSSI value in the signal reception strength sequence of each sliding window, that is, Each value in The frequency of occurrence in The calculation method is:

[0027] In the formula, Represents a counting function.

[0028] Combine the frequency values ​​corresponding to all RSSI values ​​in each sliding window to obtain the frequency vector of each sliding window :

[0029] Then the frequency vector combination of all sliding windows can construct a vector sequence :

[0030] In the formula, is the number of sliding windows; Step S3: Determine the fluctuation degree between the frequency vectors of all two adjacent sliding windows in each receiving end. , and combine all fluctuation degrees to obtain the fluctuation sequence of each receiving end : The degree of fluctuation is determined by the Euclidean distance between the frequency vectors of two sliding windows, and the formula of the fluctuation sequence R is as follows:

[0031] In the formula, and is the frequency vector of two adjacent sliding windows, is the ith fluctuation sequence.

[0032] In this embodiment, the signal reception strength at the receiving end is vectorized, and the fluctuation of the vector is determined by the Euclidean distance, thereby realizing vectorized fluctuation. This makes it possible to achieve stable and reliable calculation of fluctuation characteristics while retaining all RSSI information without causing drastic changes in values ​​that affect subsequent calculations.

[0033] Furthermore, since different wave sequences have different lengths and heights and there is random noise, in order to better match the waveform characteristics between wave sequences, before determining the similarity between each wave sequence and other wave sequences in step S3, the wave sequences are processed as follows: Each fluctuation sequence is smoothed, and the length of each fluctuation sequence is made the same through interpolation resampling method; the fluctuation sequence after interpolation resampling is normalized to 0-1.

[0034] Step S4, determining the similarity between the fluctuation sequence of each receiving end and the fluctuation sequence of other receiving ends, and adjusting the wireless sensing network topology according to the similarity.

[0035] Specifically, the similarity is determined by the Euclidean distance between the two fluctuation sequences. When , the transmitting end is adjusted to the receiving end, and the peak value of each fluctuation sequence is obtained, and the receiving end with the largest peak value is adjusted to the new transmitting end; if the Euclidean distance between the two fluctuation sequences is less than or equal to the preset threshold , no topology adjustment is performed.

[0036] In this embodiment, based on the Fresnel zone theory, the signal change characteristics caused by human activities in different Fresnel zones in a multi-node perception network can reflect its relative position. The RSSI signal in the sliding window is vectorized and the Euclidean distance between adjacent vectors is calculated to characterize the degree of signal fluctuation, so as to judge the relative position of the current target in the perception network and dynamically adjust the network topology.

[0037] The multi-node wireless sensing network topology dynamic adjustment method of the present invention is described below with specific examples.

[0038] The wireless sensing network topology includes three terminal devices equipped with Qualcomm AR9380 network card, POP!_OS 22.04 and AtherosCSI Tool, which are deployed in an indoor environment. One device is the transmitter Tx, and the other two devices are the receivers Rx1 and Rx2. Each device is 0.8m above the ground, and the devices are placed in an equilateral triangle with a spacing of 2m. The three devices are connected to the same local area network at the same time, and the sensing data of the three devices are forwarded to a terminal through data forwarding within the local area network. The terminal can be a computer as a central control device. The device is responsible for processing the sensing data from the three devices, and sending instructions to and controlling the three devices, as shown in Figure 3. Step S1, the transmitter Tx transmits a detection data packet at a rate of 500 packets / s, and the central control device obtains the detection data packets received by each receiving end Rx1 and Rx2 respectively; determines the signal reception strength of the detection data packet received by the receiving end Rx1, and uses the signal reception strength to generate the signal reception strength sequence of the receiving end Rx1 Similarly, the signal receiving strength sequence of the receiving end Rx2 is obtained ,See Figure 4 a; Step S2, set the length Set the step length to a sliding window of 50 is 50, then the signal receiving strength sequence in each sliding window is expressed as:

[0039] Since RSSI is represented as an unsigned 8-bit integer in the Atheros CSI Tool, its possible range is 0 to 255, so the RSSI element is represented as:

[0040] Determine the frequency value of each RSSI value in the signal reception strength sequence of each sliding window, that is, Each value in The frequency of occurrence in The calculation method is:

[0041] Combine the frequency values ​​corresponding to all RSSI values ​​in each sliding window to obtain the frequency vector of each sliding window :

[0042] Then the frequency vector combination of all sliding windows can construct a vector sequence :

[0043] In the formula, is the number of sliding windows; Step S3, calculate the Euclidean distance between the frequency vectors of all two adjacent sliding windows to characterize the fluctuation degree of RSSI data , and combine all the fluctuation degrees in each receiving end to obtain the fluctuation sequence of the receiving end Rx1 and the fluctuation sequence of the receiving end Rx2 ,See Figure 4 b. The fluctuation degree R of the two receiving ends is calculated by the following formula:

[0044] In the formula, and is the frequency vector of two adjacent sliding windows.

[0045] Step S4, the window size of the SG filter is set to 20, the order is set to 2, and the fluctuation sequence is filtered by the SG filter. and volatility series Smoothing is performed, as shown in FIG4c ; and the length of each fluctuation sequence is made the same through the interpolation resampling method; the fluctuation sequence after interpolation resampling is normalized to 0-1, as shown in FIG4c . Figure 4 As shown in d.

[0046] Step S5, calculate the fluctuation sequence and volatility series The Euclidean distance between According to the Fresnel zone theory, The smaller the value, the more similar the two data are. Figure 5 As shown in a, when human activity occurs near Tx, human activity will affect both Fresnel zones 1 and 2, resulting in similar signal fluctuation characteristics; on the contrary, the greater the difference, the more likely the activity is to occur near a certain Rx, such as Figure 5 As shown in b, it will cause significant differences in the signal fluctuation characteristics of the two Fresnel zones; when When it is greater than 3.2, adjust the transmitter Tx to the receiver and Figure 4 b Get the peak value of each fluctuation sequence, such as Figure 6 As shown, the receiving end Rx with the largest peak value is adjusted to the new transmitting end; if the Euclidean distance between the two fluctuation sequences is less than or equal to the preset threshold , no topology adjustment is performed.

[0047] A second embodiment of the present invention provides a multi-node wireless sensing network topology dynamic adjustment device, the wireless sensing network topology includes a transmitting end and at least two receiving ends, the device includes an acquisition module, a signal reception strength sequence generation module, a frequency vector generation module, a fluctuation sequence generation module and an adjustment module, the acquisition module is used to transmit a detection data packet through the transmitting end, and respectively obtain the detection data packet received by each receiving end; A signal reception strength sequence generation module determines the signal reception strength of the received detection data and generates a signal reception strength sequence for each receiving end; The frequency vector generation module sets a sliding window for each signal reception strength sequence, determines the frequency value of the RSSI element in each sliding window, and generates a frequency vector for each sliding window using the frequency value corresponding to the RSSI element; The fluctuation sequence generation module determines the fluctuation degree between the frequency vectors of all two adjacent sliding windows in each receiving end, and combines all the fluctuation degrees to obtain the fluctuation sequence of each receiving end; The adjustment module determines the similarity between the fluctuation sequence of each receiving end and the fluctuation sequence of other receiving ends, and adjusts the wireless sensing network topology according to the similarity.

[0048] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for dynamically adjusting the topology of a multi-node wireless sensing network, characterized in that: The wireless sensing network topology includes a transmitting end and at least two receiving ends, and the method includes: Transmitting a detection data packet through the transmitting end, and respectively obtaining the detection data packet received by each of the receiving ends; Determine the signal reception strength of the received detection data packet, and generate a signal reception strength sequence of each receiving end using the signal reception strength; Set a sliding window to determine the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window; Generate a frequency vector for each sliding window using the frequency value corresponding to the RSSI element; Determine the fluctuation degree between the frequency vectors of all two adjacent sliding windows in each receiving end, and combine all the fluctuation degrees to obtain the fluctuation sequence of each receiving end; Determine how similar the fluctuation sequence of each receiving end is to the fluctuation sequences of other receiving ends; The transmitting end and the receiving end are adjusted according to the similarity.

2. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 1, characterized in that: The RSSI element includes a plurality of RSSI values, and determining the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window, and using the frequency value corresponding to the RSSI element to generate a frequency vector of each sliding window, comprises: Determine the frequency value of each RSSI value in the signal reception strength sequence of each sliding window, combine the frequency values ​​corresponding to all RSSI values ​​in each sliding window, and obtain the frequency vector of each sliding window.

3. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 1, characterized in that: The RSSI element is represented by: ,in, is the maximum possible RSSI value, is the RSSI value.

4. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 1, characterized in that: The degree of similarity is determined by the Euclidean distance between the two fluctuation sequences.

5. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 4, characterized in that: The adjusting the transmitting end and the receiving end according to the similarity degree includes: When the Euclidean distance between two fluctuation sequences is greater than a preset threshold, the transmitting end is adjusted to the receiving end, and the peak value of each fluctuation sequence is obtained, and the receiving end with the largest peak value is adjusted to the new transmitting end.

6. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 1, characterized in that: The degree of fluctuation is determined by the Euclidean distance between the frequency vectors of two sliding windows.

7. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 1, characterized in that: The formula for the fluctuation sequence at each receiver is as follows: In the formula, is the ith fluctuation sequence, is the number of sliding windows, and is the frequency vector of two adjacent sliding windows, The degree of fluctuation.

8. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 1, characterized in that: Before determining the degree of similarity between each fluctuation sequence and other fluctuation sequences, the method further includes: Smoothing each of the fluctuation sequences, and making the lengths of each of the fluctuation sequences the same by an interpolation resampling method; The interpolated resampled fluctuation sequence is normalized to the preset interval.

9. The method for dynamically adjusting the topology of a multi-node wireless sensing network according to claim 8, characterized in that: The preset interval is 0-1.

10. A multi-node wireless sensing network topology dynamic adjustment device, characterized in that: The wireless sensing network topology includes a transmitting end and at least two receiving ends, and the device includes: An acquisition module, used for transmitting a detection data packet through the transmitting end, and respectively acquiring the detection data packet received by each of the receiving ends; A signal reception strength sequence generating module, which determines the signal reception strength of the received detection data, and generates a signal reception strength sequence of each receiving end using the signal reception strength; A frequency vector generation module sets a sliding window, determines the frequency value of the RSSI element appearing in the signal reception strength sequence of each sliding window; and generates a frequency vector of each sliding window using the frequency value corresponding to the RSSI element; The fluctuation sequence generation module determines the fluctuation degree between the frequency vectors of all two adjacent sliding windows in each receiving end, and combines all the fluctuation degrees to obtain the fluctuation sequence of each receiving end; The adjustment module determines the similarity between the fluctuation sequence of each receiving end and the fluctuation sequence of other receiving ends, and adjusts the transmitting end and the receiving end according to the similarity.

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