A method and system for maintaining a single-point location network for distributed cooperative communication

Abstract

A single-point positioning network maintenance method and system for distributed cooperative communication is disclosed. The method includes: a central node capturing network maintenance frames from member nodes in global discovery or local tracking mode and converting them into digital baseband signals; the central node demodulating and parsing the digital baseband signals to obtain network layer information and simultaneously extracting physical layer channel features and timing features; based on the physical layer channel features, calculating the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the angle of arrival; based on the timing features, triggering a hardware latching action along with a positioning gating signal to obtain the time of arrival; the central node combining the angle of arrival and time of arrival to calculate the positioning information of member nodes, fusing the positioning information and network layer information, and feeding it back to the member nodes. This method achieves high-precision single-point positioning without increasing additional hardware and signaling overhead, and integrates positioning functionality with network maintenance, improving system resource utilization.

Description

Technical Field

[0001] This invention relates to the field of wireless communication and positioning sensing technology, specifically to a method and system for maintaining a single-point positioning network for distributed cooperative communication. Background Technology

[0002] With the development of wireless communication technology, ad hoc networks, due to their characteristics of requiring no fixed infrastructure and allowing nodes to autonomously form networks, are widely used in scenarios such as vehicle-to-everything (V2X), unmanned systems networks, and emergency communications. Meanwhile, integrated sensing technology, through a unified hardware platform, achieves the fusion of communication and sensing functions, gradually becoming an important development direction for next-generation wireless systems. Existing high-precision wireless positioning technologies are mostly based on fixed base stations or multiple anchor nodes working together, typically assuming a relatively stable network topology and that communication, sensing, and positioning functions are independent. In ad hoc network environments, due to nodes autonomously joining, leaving, and moving, the network topology changes frequently, making traditional positioning methods relying on multi-node collaboration or centralized processing difficult to adapt to dynamic networking scenarios. Furthermore, to achieve high-precision positioning, existing technologies often require additional positioning signals or dedicated hardware modules, increasing system complexity and deployment costs. On the other hand, during the operation of ad hoc networks, to maintain network connectivity and normal communication, nodes need to continuously perform network maintenance, including neighbor discovery, time synchronization, link status updates, and topology maintenance, generating a large amount of network maintenance information during these processes. However, existing positioning schemes typically fail to integrate the aforementioned network maintenance information with positioning functions, thus failing to fully utilize the information generated during the normal operation of the sensor-integrated self-organizing network, resulting in low network resource utilization efficiency. In a dynamic self-organizing network environment, achieving stable, high-precision single-point positioning without increasing additional hardware and signaling overhead remains a pressing technical problem to be solved.

[0003] Existing technologies, particularly signal strength-based positioning methods, which are widely used for accuracy and interference resistance, are highly susceptible to multipath effects and shadowing fading in the complex electromagnetic environment of ad hoc networks, leading to large and unstable ranging errors. Furthermore, existing methods primarily cater to centrally located processing nodes with abundant computing resources. In highly dynamic ad hoc network scenarios, nodes struggle to handle the complex complex matrix operations, resulting in large location calculation delays, low refresh rates, and location awareness information lagging behind rapid changes in network topology, failing to meet the demands of real-time topology control. In addition, existing solutions typically treat network maintenance and positioning as two independent processes, failing to leverage the physical layer features in network maintenance frames (such as Hello packets). This necessitates additional spectrum or hardware resources to support positioning, reducing the resource utilization of the integrated sensing platform.

[0004] Shixun Wu (EURASIP Journal on Wireless Communications and Networking, 2022, Article number: 4) proposed a single-base-station hybrid TOA / AOD / AOA localization algorithm with synchronization error in dense multipath environments. This scheme uses a hybrid approach, combining time of arrival (TOA), departure angle (DOA), and angle of arrival (AOA) measurements, and proposes four linear least squares algorithms, one quadratic programming algorithm, and a data fusion-based localization algorithm to address the localization problem of a single serving base station for a mobile station in dense multipath environments and mitigate the impact of synchronization errors. It achieves good localization accuracy in both one-hop and multi-hop scattering environments and effectively eliminates synchronization errors. However, the method still relies on traditional multipath parameter estimation techniques, resulting in high computational complexity in highly dynamic scenarios. It requires independent angle and time delay estimation for each scattering path, making real-time processing difficult in ad hoc network environments. Furthermore, the scheme does not consider integrating the localization function with network maintenance processes, requiring additional measurement signaling overhead, leading to low system efficiency in ad hoc network scenarios with limited spectrum resources. Summary of the Invention

[0005] To overcome the shortcomings of the existing technologies, the present invention aims to provide a single-point positioning network maintenance method and system for distributed cooperative communication. This method solves the problems of difficulty in achieving stable high-precision single-point positioning in dynamic self-organizing network environments without increasing additional hardware and signaling overhead, and low system resource utilization caused by the independence of positioning and network maintenance functions. It achieves the effect of deep integration of communication and positioning perception, and closed-loop coordination of network maintenance and topology update. It has the advantages of high accuracy, low overhead, strong robustness, good real-time performance, and easy deployment and implementation on FPGA platform.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for maintaining a single-point location network for distributed cooperative communication includes the following steps: Step 1: The central node adaptively adjusts the beam scanning strategy according to the routing status, captures the network maintenance frames sent by member nodes in global discovery or local tracking mode, and converts the network maintenance frames into digital baseband signals; Step 2: The central node demodulates and parses the digital baseband signal to obtain network layer information, and simultaneously extracts the physical layer channel characteristics of the network maintenance frame and the timing characteristics of the digital baseband signal. Step 3: Based on the physical layer channel characteristics of the network maintenance frame, calculate the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the angle of arrival (AOA). Step 4: Based on the timing characteristics of the digital baseband signal, trigger the hardware latching action together with the positioning gating signal to obtain the arrival time TOA; Step 5: The central node calculates the location information of the member nodes by combining the angle of arrival (AOA) and time of arrival (TOA), and then feeds back the location information and network layer information to the member nodes to complete network maintenance.

[0007] Furthermore, step 1 specifically includes: Step 1.1: Member nodes periodically broadcast network maintenance frames; Step 1.2: The central node maintains the routing table state machine in real time through its internal FPGA beam scanning controller; Step 1.3: The central node determines the link status of the member nodes based on the routing table state machine, and executes global discovery or local tracing mode to capture the network maintenance frames sent by the member nodes; Step 1.4: After the central node captures the network maintenance frame through the radio frequency front end, it converts the network maintenance frame into a digital baseband signal.

[0008] Furthermore, step 1.3 specifically includes: The central node checks if a valid record of the target member node exists in its local routing table; if no target member node exists in the local routing table, or if the last active time of a member node exceeds a preset time threshold T. timeout If the target member node exists in the local routing table, it indicates that the link is connected. If the central node is in a disconnected or lost link state, it enters global discovery mode, specifically as follows: The central node generates a set of orthogonal beam weight vectors W={w} through an FPGA beam scanning controller. 1, w2,...,w M}; where M is the total number of beams required for omnidirectional coverage; The central node controls the phase shifter of the radio frequency front end to quickly poll the M beam directions in the order of the orthogonal beam weight vector set W during the reception period of each network maintenance frame in order to capture network maintenance frames from any spatial direction. If the link is connected, the central node will receive the latest angle information θ from the network maintenance frame of the target member node.curr Update the local routing table, set the system status flag to connected, and enter local tracing mode, specifically: In the next network maintenance frame reception cycle, the central node reads the previous historical angle information θ of the target member node from its local routing table. last ; Instead of traversing all beams in the orthogonal beam weight vector set W, the FPGA beam scanning controller generates a local neighborhood subset of beams. The local neighborhood beam subset Including historical angle θ last The beam scanning range is limited to the K beams to its left and right, and the K beams adjacent to it. Within the interval; where, For a single beam, 3dB width This is the preset tracking window coefficient.

[0009] Furthermore, in step 2, the central node demodulates and parses the digital baseband signal to obtain network layer information, specifically including: Time-frequency synchronization and channel equalization processing are performed on digital baseband signals; The digital baseband signal, after time-frequency synchronization and channel equalization processing, is decoded according to the preset encoding rules to obtain the information bit sequence; The central node parses the network layer information from the information bit sequence.

[0010] Furthermore, step 2, which involves synchronously extracting the physical layer channel features of the network maintenance frame and the timing features of the digital baseband signal, specifically includes: The central node extracts physical layer channel features, including signal-to-noise ratio (SNR) and beam index, from the network maintenance frame: During the preamble stage of receiving the network maintenance frame, the central node uses its internal energy detector to calculate the SNR in real time within the current received beam. dB During beam scanning, the central node maintains a set of registers to store the maximum signal-to-noise ratio (SNR). max and its corresponding beam index ID max Second largest signal-to-noise ratio (SNR) sec and its corresponding beam index ID sec ; The central node extracts timing features, including synchronization pulses, from the digital baseband signal: the central node compares the digital baseband signal with the locally pre-stored standard synchronization word sequence. Perform cross-correlation calculations to obtain the cross-correlation peak value. The modulus of the cross-correlation peak value monitored by the central node | |, if the modulus| |Exceeding the preset judgment threshold At this point, the central node determines that synchronization is successful and generates a synchronization pulse. .

[0011] Furthermore, step 3 specifically includes: Step 3.1: The central node reads the registered maximum signal-to-noise ratio (SNR) in the logarithmic domain. max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain sec Then, the maximum signal-to-noise ratio (SNR) in the logarithmic domain is obtained by using the exponential transformation formula. max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain sec Convert to the maximum signal-to-noise ratio (SNRmax_line) and the second-largest signal-to-noise ratio (SNRsec_line) in the linear domain; the correlation index conversion formula is: Step 3.2: Calculate the energy ratio factor η based on the maximum signal-to-noise ratio (SNRmax_line) in the linear domain and the second-largest signal-to-noise ratio (SNRsec_line) in the linear domain; the relevant calculation formula is as follows: Step 3.3: The central node reads the registered beam index ID. max With beam index ID sec Compare beam index IDs max With beam index ID sec The relative position is used to determine the interpolation direction. :like If the secondary strong signal is located to the left of the main beam, it is marked. ;like If the secondary strong signal is located to the right of the main beam, it is marked. ; Step 3.4: The central node uses the energy ratio factor η as the index address to query its internally stored fine-tuning mapping table and outputs the corresponding angle deviation. ; Step 3.5: The central node is based on the beam index ID. max Interpolation direction , angle deviation Calculate the angle of arrival (AOA); the relevant calculation formula is as follows: in, Beam Index ID max The corresponding physical center pointing angle.

[0012] Furthermore, step 4 specifically includes: Step 4.1: The central node monitors the physical state of the current receiving beam in real time, and sets the positioning gate signal Gate_En to an active level only when both decision conditions are met simultaneously; Step 4.2: Match the positioning gate signal Gate_En with the synchronization pulse of the timing characteristics. Perform an AND logical operation to obtain the system-defined trigger signal. The relevant calculation expression is: Step 4.3: The FPGA of the central node maintains a counter with a counting frequency of f. clk When the system defines a trigger signal When a rising edge is detected, the current count value T of the counter is... cnt It was instantly latched into the TOA data register; Step 4.4: The central node performs delay compensation on the arrival time (TOA) latched in the TOA data register; the relevant calculation expression is: in, This is the hardware group latency compensation value.

[0013] Furthermore, the two decision conditions in step 4.1 include a signal-to-noise ratio (SNR) condition and a direct beam path characteristic condition; the SNR condition is the currently detected beam SNR. It must be greater than the preset quality threshold. The direct beam characteristic condition is the currently detected beam temporal width. It must be smaller than the preset width threshold. .

[0014] Furthermore, step 5 specifically includes: Step 5.1: The central node reads the angle of arrival. And arrival time (TOA), convert the arrival time (TOA) to distance. Then, the coordinates of the member nodes are calculated using the transformation formula from spherical coordinates to Cartesian coordinates. The transformation formula from the spherical coordinate system to the Cartesian coordinate system is as follows: in, At the speed of light, It is the azimuth angle. Angle of elevation; Step 5.2: The central node calculates the coordinates of the member nodes. Update the local routing table and construct a topology response frame, using network layer information to specify the coordinates of member nodes. Encapsulated in the data payload, the topology response frame is sent back to the member node in the next communication time slot; Step 5.3: After receiving the topology response frame, the member node parses the topology response frame to obtain its own position relative to the central node. Based on its own position relative to the central node, the member node performs formation maintenance, path planning, or transmission power adjustment to complete network maintenance.

[0015] A single-point location network maintenance system for distributed cooperative communication includes: Adaptive beam scanning and signaling capture module: The central node adaptively adjusts the beam scanning strategy according to the routing status, captures the network maintenance frames sent by member nodes in global discovery or local tracking mode, and converts the network maintenance frames into digital baseband signals; Parallel extraction module for communication sensing features: The central node demodulates and parses the digital baseband signal to obtain network layer information, and simultaneously extracts the physical layer channel features of the network maintenance frame and the timing features of the digital baseband signal; Angle of Arrival (AOA) Module: Based on the physical layer channel characteristics of the network maintenance frame, the module calculates the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the AOA. Hardware-gated arrival time latch module: Based on the timing characteristics of the digital baseband signal, it triggers a hardware latching action together with the positioning gating signal to obtain the arrival time (TOA). Location calculation and topology closed-loop maintenance module: The central node calculates the location information of member nodes by combining the angle of arrival (AOA) and time of arrival (TOA), and then feeds back the location information and network layer information to the member nodes to complete network maintenance.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. In step 3 of this invention, when calculating the angle deviation exceeding the physical beam resolution using an interpolation algorithm, the energy ratio factor η calculated using the maximum signal-to-noise ratio SNR_max and the second-largest signal-to-noise ratio SNR_sec is used as the index address to query the pre-stored fine-tuning mapping table inside the FPGA and output the corresponding angle deviation. And combined with interpolation direction Dir and beam index ID maxThe corresponding physical center pointing angle synthesized angle of arrival (AOA) solves the problems in existing technologies where beam scanning angle measurement accuracy is rigidly limited by the physical antenna aperture, angle resolution is locked at the single beamwidth level, and it is impossible to break through the lower limit of accuracy without increasing the array size. It achieves a high-precision angle of arrival estimation effect that surpasses the physical beam resolution without introducing any additional antenna elements or matrix eigenvalue decomposition operations (the root mean square error of angle measurement is reduced from 4.8 in the traditional method to 1.1° when the signal-to-noise ratio is 10dB, and the accuracy is improved by about 77.1%). It has the advantages of low computational complexity, real-time implementation on FPGA, and low hardware resource consumption.

[0017] 2. In step 4 of this invention, when the hardware latching action is triggered together with the positioning gating signal, two decision conditions are set, and only when the beam signal-to-noise ratio is... Greater than the preset quality threshold And beam temporal width It must be smaller than the preset width threshold. At this time, the gate signal Gate_En and the synchronization pulse Sync_Pulse perform an AND operation to form the system-defined trigger signal. This drives the time delay compensation of the arrival time (TOA) latched in the TOA data register, solving the problems of traditional RSSI ranging methods being easily affected by multipath effects and shadow fading in complex electromagnetic environments, having large ranging errors, and not improving significantly with signal-to-noise ratio (errors as high as 16.5 meters at low signal-to-noise ratios). It achieves the effect of effectively eliminating multipath reflection signals and completing nanosecond-level precision TOA acquisition at the physical layer at the signal arrival time (the ranging error is stable within 2 meters when the signal-to-noise ratio is greater than 10dB). It has the advantages of strong anti-multipath capability, high ranging accuracy, good robustness, and the ability to maintain stable and high-precision distance measurement in complex electromagnetic environments.

[0018] 3. In step 1 of this invention, when adaptively adjusting the beam scanning strategy according to the routing state and capturing network maintenance frames sent by member nodes in global discovery or local tracking mode, the FPGA beam scanning controller no longer traverses all beams in the orthogonal beam weight vector set W, but instead generates a beam containing historical angles θ. last Local neighborhood beam subsets of the beams and their left and right adjacent K beams That is, limiting the beam scanning range to Within the range, the entire scan cycle is shortened to that of global mode. By combining the physical layer channel features of the network maintenance frame and the timing features of the digital baseband signal extracted synchronously in step 2, this approach solves the problems of existing positioning schemes that treat network maintenance and positioning functions as independent processes, fail to reuse the physical layer features of the network maintenance frame, require additional spectrum resources or dedicated hardware support, and suffer from large location calculation delays, low refresh rates, and inability to meet real-time topology control requirements in highly dynamic scenarios. This approach achieves the effect of fully embedding the positioning function into the network maintenance process and realizing a closed loop of integrated communication and positioning without adding any additional hardware modules or dedicated positioning signaling. It has the advantages of high system integration, high spectrum resource utilization, low deployment cost, and adaptability to highly dynamic self-organizing network scenarios.

[0019] In summary, this invention solves the problems of difficulty in achieving stable single-point high-precision positioning in dynamic self-organizing network environments without increasing additional hardware and signaling overhead, and the low system resource utilization caused by the independence of positioning and network maintenance functions, through adaptive beam scanning, parallel extraction of communication sensing features, sub-beam level energy ratio interpolation angle measurement, and dual-condition hardware-gated nanosecond-level TOA latching technology. It achieves the effect of deep integration of communication and positioning sensing, and closed-loop coordination of network maintenance and topology update, and has the advantages of high accuracy, low overhead, strong robustness, good real-time performance, and easy deployment and implementation on FPGA platform. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the single-point location network maintenance method for distributed cooperative communication according to the present invention. Figure 1 .

[0021] Figure 2 This is a flowchart illustrating the single-point location network maintenance method for distributed cooperative communication according to the present invention. Figure 2 .

[0022] Figure 3 This is a schematic diagram of the frame format of the network maintenance frame of the present invention.

[0023] Figure 4 This is a schematic diagram of the frame format of the topology response frame of the present invention.

[0024] Figure 5 This is a comparison diagram of the single-point positioning network maintenance method of the present invention and the traditional beam scanning method in terms of angle measurement accuracy.

[0025] Figure 6 This is a comparison diagram of the single-point positioning network maintenance method of the present invention and the traditional beam scanning method in terms of ranging error. Detailed Implementation

[0026] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments: See Figure 1 and Figure 2 A method for maintaining a single-point location network for distributed cooperative communication includes the following steps: Step 1: The central node adaptively adjusts its beam scanning strategy based on the routing status, captures network maintenance frames (Hello Packets) sent by member nodes in global discovery or local tracking mode, and converts the network maintenance frames into digital baseband signals. ; This invention is applied to self-organizing network scenarios that include a central node and member nodes. The internal architecture of the central node comprises three main modules: an external hardware interface layer, a core processing layer (based on FPGA), and a control and decision-making layer. The functions and collaborative relationships of each module are as follows: External Hardware Interface Layer: As the signal interaction interface between the central node and the outside world, it is responsible for the transmission and reception and preprocessing of wireless signals. Specifically, it includes: Radio Frequency Front-End: It undertakes bidirectional wireless communication functions, receiving wireless radio frequency signals carrying network maintenance frames sent by member nodes, and transmitting control commands from the central node. It is the core interface for link signal interaction; Phase Shifter: It responds to beam scanning commands issued by the core processing layer, dynamically adjusts the beam direction, realizes accurate alignment and real-time tracking of member nodes, and supports detection mode switching. Transmitter interleaver: performs interleaving and encoding processing on the control commands and data signals to be transmitted, improving the anti-interference robustness of signal transmission and ensuring the reliability of data transmission; Analog-to-digital converter (ADC): converts the analog intermediate frequency signal output from the RF front end into a digital signal, providing input for the subsequent digital signal processing of the core processing layer.

[0027] Core Processing Layer (FPGA-based): This layer serves as the core computing and signal processing unit for the central node. It integrates various functional modules and parallel processing branches, specifically including: an energy detector, a demodulation module, an FPGA beam scanning controller, dual parallel branches for communication data demodulation and positioning feature extraction, an arithmetic logic unit (ALU), and an embedded processing unit. The energy detector interfaces with the digital signal output from the analog-to-digital converter module, detecting signal energy intensity in real time, filtering valid signals and eliminating invalid noise, and extracting signal energy factors. This provides a basis for judging the signal validity for the demodulation module's demodulation actions. The system supplements energy feature data for the positioning feature extraction branch; the demodulation module demodulates the effective digital signal based on the energy detector's preprocessing, restoring the original information carried by the signal and providing qualified signal input for subsequent dual-branch parallel processing; the sliding correlator module, integrated within the FPGA, interfaces with the effective digital signal output from the energy detector, achieving synchronous signal acquisition and symbol synchronization calibration through sliding correlation operations, while also assisting in the extraction of signal timing features (such as TOA), providing accurate synchronization support for the timing feature calculation of the positioning feature extraction branch and improving positioning accuracy; the FPGA beam scanning controller drives the beam shift... The phase detector performs beam scanning in "global discovery" or "local tracking" modes, simultaneously capturing physical layer wireless signals; dual-branch parallel processing: with the cooperation of the demodulation module, the communication data demodulation branch is responsible for demodulating and decoding the captured signals to restore network layer data; the positioning feature extraction branch is responsible for simultaneously extracting signal timing features (such as TOA) and link state features (such as SNR), providing data support for link quality judgment; the arithmetic logic unit (ALU) undertakes core mathematical operations such as cross-correlation and coordinate calculation, providing computing power support for signal feature extraction and positioning calculation; embedded processing unit: Integrated within the FPGA, this core unit serves as the core collaborative control and data management unit of the core processing layer. On one hand, it coordinates the runtime sequence of various functional modules, such as the energy detector, demodulation module, and sliding correlator module, and coordinates signal interaction and data flow between modules to avoid processing conflicts. On the other hand, it is responsible for storing intermediate data, calculation parameters, and final feature data during the processing, connecting the calculation results of the arithmetic logic unit with the processing requirements of the dual parallel branches, and simultaneously providing feedback on the module's operating status. This improves the operating efficiency, data processing continuity, and stability of the core processing layer, providing reliable control and data support for link quality judgment and positioning calculation.

[0028] Control and Decision Layer: Responsible for link status determination, detection mode switching, and route maintenance, it is the control core of the central node. Specifically, it includes: a gating decision module: which dynamically determines link quality and triggers the switching between "global discovery" and "local tracking" modes by integrating signal characteristics output from the core processing layer, frame parsing results, and the current state of the routing table state machine; and a routing table and routing table state machine: the routing table stores topology information, link parameters, and valid records of member nodes; the routing table state machine represents the connection lifecycle of each member node (e.g., initialization, connection, and link disconnection states). These two work together to support the central node in efficiently completing route maintenance and link fault detection.

[0029] Step 1 specifically includes: Step 1.1: Member nodes periodically broadcast network maintenance frames for neighbor discovery and route maintenance; the frame format of the network maintenance frame is as follows: Figure 3 As shown, it includes: preamble, synchronization word, frame type identifier, source node ID, message sequence number and check bit, wherein the message sequence number is incremented by 1 each time a network maintenance frame is sent; Step 1.2: The central node maintains the routing table state machine in real time through its internal FPGA beam scanning controller; Step 1.3: The central node determines the link status of the member nodes based on the routing table state machine, and executes global discovery or local tracing mode to capture the network maintenance frames sent by the member nodes; Step 1.3 specifically includes: The central node checks if a valid record of the target member node exists in its local routing table; if no target member node exists in the local routing table, or if the last active time of a member node exceeds a preset time threshold T. timeout If the target member node exists in the local routing table, it indicates that the link is connected; if the target member node exists in the local routing table, it indicates that the link is connected; the time threshold T in this embodiment... timeout It lasts for 5 seconds; If the central node is in a disconnected or lost link state, it enters global discovery mode, specifically as follows: The central node generates a set of orthogonal beam weight vectors W={w} through an FPGA beam scanning controller. 1, w2,...,w M}; where M is the total number of beams required for omnidirectional coverage; in this embodiment, M is ; The central node controls the phase shifter of the radio frequency front end to quickly poll the M beam directions in the order of the orthogonal beam weight vector set W during the reception period of each network maintenance frame in order to capture network maintenance frames from any spatial direction. If the link is connected, the central node will receive the latest angle information θ from the network maintenance frame of the target member node. curr Update the local routing table, set the system status flag to connected, and enter local tracing mode, specifically: In the next network maintenance frame reception cycle, the central node reads the previous historical angle information θ of the target member node from its local routing table. last ; Instead of traversing all beams in the orthogonal beam weight vector set W, the FPGA beam scanning controller generates a local neighborhood subset of beams. The local neighborhood beam subset Including historical angle θ last The beam scanning range is limited to the K beams to its left and right, and the K beams adjacent to it. Within the interval, where, It is a 3dB width for a single beam (half-power beamwidth). In this embodiment, the preset tracking window coefficient is used. That is, a total of 5 beams are scanned; Using the above method, the central node utilizes the prior location information from the routing table to shorten the spatial scan cycle to that of global mode. This enables the tracking of high-speed moving ad hoc network nodes with higher time resolution.

[0030] Step 1.4: After the central node captures the network maintenance frame through the radio frequency front end, it converts the network maintenance frame into a digital baseband signal. In this embodiment, the analog-to-digital converter at the central node is used to convert network maintenance frames into digital baseband signals. .

[0031] Step 2: While the central node demodulates and parses the digital baseband signal to obtain network layer information, it simultaneously extracts the physical layer channel characteristics of the network maintenance frame and the timing characteristics of the digital baseband signal. In this embodiment, the RF front-end captures a network maintenance frame and converts it into a digital baseband signal via an analog-to-digital converter. Subsequently, the physical layer receiving pipeline inside the central node initiates a dual-parallel processing mechanism, performing the following processing via the communication data demodulation branch and the positioning feature extraction branch respectively: 2a) Communication data demodulation branch processing In step 2, the central node demodulates the digital baseband signal and performs protocol parsing to obtain network layer information, specifically including: For digital baseband signals Perform time-frequency synchronization and channel equalization processing; The digital baseband signal, after time-frequency synchronization and channel equalization processing, is processed according to the preset coding rules. Perform a decoding operation to obtain the information bit sequence, specifically: Based on the QPSK modulation method, the digital baseband signal after time-frequency synchronization and channel equalization processing is... Make a decision, and then map the complex baseband signal obtained after the decision into a discrete symbol sequence; The discrete symbol sequence is converted into a recovered sequence by reversing the order of the interleaver at the transmitting end; By searching for the maximum likelihood path using a grid graph and employing a convolutional code with R=1 / 2 and K=7, the recovered sequence is corrected, and the information bit sequence is output.

[0032] The demodulation module at the central node parses the network layer information from the information bit sequence, specifically as follows: Frame synchronization is achieved by detecting the frame header identifier code; Fields are extracted from the information bit sequence according to byte offset and length. The extracted fields include source node ID and sequence number (used to determine the timeliness of routing information). The extracted network layer information, including the source node ID and sequence number, is temporarily stored in the FIFO buffer of the central node, awaiting subsequent fusion with the location information.

[0033] 2b) Localization Feature Extraction Branch Processing This branch is mainly used to extract spatial energy features and high-precision temporal features from physical layer signals, and specifically includes the following two parallel processes: In step 2, the physical layer channel features and digital baseband signals of the network maintenance frame are extracted synchronously. The specific temporal characteristics include: The central node extracts physical layer channel features, including signal-to-noise ratio (SNR) and beam index, from the network maintenance frame: During the preamble stage of receiving the network maintenance frame, the central node uses its internal energy detector to calculate the SNR in real time within the current received beam. dB The relevant calculation formulas are as follows: in, This indicates the number of sampling points used for energy accumulation calculation. Indicates the first The amplitude of the received signal at each sampling time, The receiver thermal noise floor power is used for pre-calibration or real-time measurement of the system. During beam scanning, the central node maintains a set of registers to store the maximum signal-to-noise ratio (SNR). max and its corresponding beam index ID max Second largest signal-to-noise ratio (SNR) secand its corresponding beam index ID sec Specifically: During beam scanning, each beam is calculated... The central node compares the current value with the value stored in the register: if the current value is... If the value is greater than the maximum value in the register, then update the maximum signal-to-noise ratio. and its corresponding beam index The original maximum value in the register is then shifted to the second largest signal-to-noise ratio. and its corresponding suboptimal beam index This process ensures that at the end of the scan, the system is able to acquire the critical energy parameters used for subsequent subbeam interpolation.

[0034] The central node receives digital baseband signals. Extracting timing features including synchronization pulses from the central node's digital baseband signal. and the locally stored standard synchronization word sequence Perform cross-correlation calculations to obtain the cross-correlation peak value. In this embodiment, the sliding correlator module inside the FPGA of the central node performs real-time cross-correlation calculations, and the correlation calculation formula is as follows: in, Indicates the sliding time delay. Indicates the sequence length of the synchronization word. Indicates the local synchronization sequence number The complex conjugate of elements; The modulus of the cross-correlation peak value monitored by the central node | |, if the modulus| |Exceeding the preset judgment threshold At this point, the central node determines that synchronization is successful and generates a synchronization pulse. This pulse marks the precise end time of the physical layer synchronization field of the network maintenance frame, serving as one of the trigger signals for subsequent hardware latch arrival time (TOA); this embodiment exceeds a preset decision threshold. It is 0.75, that is, when the modulus of the cross-correlation peak is | When the theoretical peak value is reached by 75%, synchronization is considered successful.

[0035] Step 3: Based on the physical layer channel characteristics of the network maintenance frame, calculate the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the angle of arrival (AOA). Step 3 specifically includes: Step 3.1: The central node reads the registered maximum signal-to-noise ratio (SNR) in the logarithmic domain. max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain secThen, the maximum signal-to-noise ratio (SNR) in the logarithmic domain is obtained by using the exponential transformation formula. max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain sec The maximum signal-to-noise ratio (SNR) in the linear domain (SNRmax_line) and the second-largest signal-to-noise ratio (SNRsec_line) in the linear domain are converted. In this embodiment, the central node calls the arithmetic logic unit inside the FPGA when reading the SNR. The formula for converting related indices is: Step 3.2: Based on the maximum signal-to-noise ratio (SNR) in the logarithmic domain max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain sec Calculate the energy ratio factor η; the relevant calculation formula is as follows: Step 3.3: The central node reads the registered beam index ID. max With beam index ID sec Compare beam index IDs max With beam index ID sec The relative position is used to determine the interpolation direction. :like If the secondary strong signal is located to the left of the main beam, it is marked. ;like If the secondary strong signal is located to the right of the main beam, it is marked. In this embodiment, the central node calls the arithmetic logic unit inside the FPGA when reading the beam index. Step 3.4: The central node uses the energy ratio factor η as the index address to query its internally stored fine-tuning mapping table and outputs the corresponding angle deviation. In this embodiment, to obtain angular deviations exceeding the physical beam resolution, the central node calls a fine-tuning mapping table pre-stored in its FPGA. This mapping table establishes the energy ratio. and angular deviation value The nonlinear correspondence between them; Step 3.5: The central node is based on the beam index ID. max Interpolation direction , angle deviation Calculate the angle of arrival (AOA); the relevant calculation formula is as follows: in, Beam Index ID max The corresponding physical center pointing angle.

[0036] Through step 3.5, this embodiment can achieve sub-beam-level angle measurement accuracy without increasing additional computing resources (such as matrix eigenvalue decomposition).

[0037] Step 4: Based on the timing characteristics of the digital baseband signal, trigger the hardware latching action together with the positioning gating signal to obtain the arrival time TOA; Furthermore, step 4 specifically includes: Step 4.1: The central node monitors the physical state of the current receiving beam in real time. Only when both decision conditions are met simultaneously, the positioning gate signal Gate_En is set to an active level. In this embodiment, when the central node monitors the physical state of the current receiving beam in real time, it calls the central node's gate decision module. The two decision conditions in step 4.1 include the signal-to-noise ratio (SNR) condition and the direct beam path characteristic condition; the SNR condition is the currently detected beam SNR. It must be greater than the preset quality threshold. To ensure that the signal quality meets the ranging requirements; the direct beam characteristic condition is the currently detected beam temporal width. It must be smaller than the preset width threshold. This is used to eliminate reflection path interference; the preset quality threshold in this embodiment It is 5dB.

[0038] Step 4.2: Match the positioning gate signal Gate_En with the synchronization pulse of the timing characteristics. Perform an AND logical operation to obtain the system-defined trigger signal. The relevant calculation expression is: Step 4.3: The FPGA of the central node maintains a high-precision, freely running counter with a counting frequency of f. clk When the system defines a trigger signal When a rising edge is detected, the current count value T of the counter is... cnt It was instantly latched into the TOA data register; Step 4.4: The central node performs delay compensation on the arrival time (TOA) latched in the TOA data register, specifically as follows: Considering the slight differences in the path length of the RF channel circuit corresponding to different beam directions of the phased array antenna, a "channel delay table" is pre-stored inside the central node. The central node determines the channel delay based on the current beam index. Query the "Channel Delay Table" to obtain the corresponding hardware group delay compensation value. And perform time delay compensation operation on TOA; the relevant calculation expression is: in, This is the hardware group latency compensation value.

[0039] Step 5: The central node calculates the location information of the member nodes by combining the angle of arrival (AOA) and time of arrival (TOA), and then feeds back the location information and network layer information to the member nodes to complete network maintenance.

[0040] Step 5 specifically includes: Step 5.1: The central node reads the angle of arrival. And arrival time (TOA), convert the arrival time (TOA) to distance. Then, the coordinates of the member nodes are calculated using the transformation formula from spherical coordinates to Cartesian coordinates. In this embodiment, the central node reads the arrival angle. The arrival time (TOA) is used to invoke the embedded processing unit of the central node; The transformation formula from the spherical coordinate system to the Cartesian coordinate system is as follows: in, The speed of light; It is the azimuth angle. Angle of elevation; Step 5.2: The central node calculates the coordinates of the member nodes. Update the local routing table for use by subsequent routing optimization algorithms; to achieve closed-loop network maintenance, a topology response frame is also constructed, using network layer information to specify the coordinates of member nodes. Encapsulated in the data payload, the topology response frame is sent back to the member node in the next communication time slot; Step 5.3: After receiving the topology response frame, the member nodes parse the frame to obtain their position relative to the central node. Based on their position relative to the central node, the member nodes perform formation maintenance, path planning, or transmit power adjustment to complete network maintenance. In this embodiment, the frame format of the topology response frame is as follows: Figure 4 As shown, it includes: source node ID, destination node ID, frame type, X, Y, Z coordinate data and check bits.

[0041] A single-point location network maintenance system for distributed cooperative communication includes: Adaptive beam scanning and signaling capture module: The central node adaptively adjusts the beam scanning strategy according to the routing status, captures the network maintenance frames sent by member nodes in global discovery or local tracking mode, and converts the network maintenance frames into digital baseband signals; Parallel extraction module for communication sensing features: The central node demodulates and parses the digital baseband signal to obtain network layer information, and simultaneously extracts the physical layer channel features of the network maintenance frame and the timing features of the digital baseband signal; Angle of Arrival (AOA) Module: Based on the physical layer channel characteristics of the network maintenance frame, the module calculates the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the AOA. Hardware-gated arrival time latch module: Based on the timing characteristics of the digital baseband signal, it triggers a hardware latching action together with the positioning gating signal to obtain the arrival time (TOA). Location calculation and topology closed-loop maintenance module: The central node calculates the location information of member nodes by combining the angle of arrival (AOA) and time of arrival (TOA), and then feeds back the location information and network layer information to the member nodes to complete network maintenance.

[0042] The application effects of this invention will be described in detail below with reference to simulation experiments: This invention uses a MATLAB and Vivado co-simulation platform to compare the performance differences in angle measurement accuracy and distance measurement accuracy between the single-point positioning network maintenance method proposed in this invention and the traditional physical beam scanning method (for angle measurement) and RSSI ranging method (for distance measurement) under different signal-to-noise ratio (SNR) environments. The parameters set during the simulation are shown in Table 1.

[0043] Table 1 Simulation Parameter Table carrier frequency 5.8 GHz Antenna Array 8×8 UPA System bandwidth 100 MHz beamwidth Approximately 6° Channel Model Multipath Rayleigh fading Maximum multipath delay 50 ns SNR range -5dB ~ 25dB Sampling rate 400 MHz See Figure 5 As the signal-to-noise ratio (SNR) increases, the angle measurement error of both methods decreases. However, at the same SNR, the angle measurement accuracy based on the invention is significantly better than that of the traditional beam scanning method. When the SNR is 10 dB, the root mean square error (RMSE) of the angle measurement of the traditional beam scanning method is approximately 3.6°, while the RMSE of the angle measurement based on the invention is reduced to 0.48°, improving the accuracy by approximately 86.7%. The main reason for this is that the traditional method is limited by the physical aperture of the antenna, and its resolution is restricted to the order of beamwidth (approximately 6°), resulting in a significant lower limit to accuracy. In contrast, the invention utilizes the energy ratio of adjacent beams for sub-beam level interpolation correction, breaking through the resolution limitation of the physical beam, thereby achieving high-precision angle sensing without increasing the size of the antenna array. In summary, the invention can achieve high-precision angle measurement with limited hardware resources compared to the traditional method.

[0044] See Figure 6Compared to traditional RSSI ranging methods, this invention effectively resists multipath effects and significantly reduces ranging errors. In low signal-to-noise ratio (SNR) environments (e.g., 0 dB), the ranging error of traditional RSSI methods is as high as 16.5 meters, and the improvement is not significant with increasing SNR. In contrast, the ranging error based on this invention is only 3.2 meters, and it remains stable within 1 meter when the SNR is greater than 10 dB. This is because traditional RSSI methods are highly susceptible to multipath fading and shadowing effects, resulting in drastic fluctuations in signal strength and an inability to accurately reflect the true distance. This invention designs a hardware-gated latching mechanism, combining SNR and direct beamwidth characteristics to effectively eliminate multipath reflection signals, and utilizes physical layer synchronization words to trigger nanosecond-level hardware latching. Therefore, this invention has stronger robustness than RSSI methods and can maintain high-precision distance measurement in complex electromagnetic environments.

[0045] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions or improvements made by those skilled in the art within the spirit and principles of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for maintaining a single-point location network for distributed cooperative communication, characterized in that: Specifically, the steps include the following: Step 1: The central node adaptively adjusts the beam scanning strategy according to the routing status, captures the network maintenance frames sent by member nodes in global discovery or local tracking mode, and converts the network maintenance frames into digital baseband signals; Step 2: The central node demodulates and parses the digital baseband signal to obtain network layer information, and simultaneously extracts the physical layer channel characteristics of the network maintenance frame and the timing characteristics of the digital baseband signal. Step 3: Based on the physical layer channel characteristics of the network maintenance frame, calculate the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the angle of arrival (AOA). Step 4: Based on the timing characteristics of the digital baseband signal, trigger the hardware latching action together with the positioning gating signal to obtain the arrival time TOA; Step 5: The central node calculates the location information of the member nodes by combining the angle of arrival (AOA) and time of arrival (TOA), and then feeds back the location information and network layer information to the member nodes to complete network maintenance.

2. The method for maintaining a single-point location network for distributed cooperative communication according to claim 1, characterized in that: Step 1 specifically includes: Step 1.1: Member nodes periodically broadcast network maintenance frames; Step 1.2: The central node maintains the routing table state machine in real time through its internal FPGA beam scanning controller; Step 1.3: The central node determines the link status of the member nodes based on the routing table state machine, and executes global discovery or local tracing mode to capture the network maintenance frames sent by the member nodes; Step 1.4: After the central node captures the network maintenance frame through the radio frequency front end, it converts the network maintenance frame into a digital baseband signal.

3. A single-point location network maintenance method for distributed cooperative communication according to claim 2, characterized in that: Step 1.3 specifically includes: The central node checks if a valid record of the target member node exists in its local routing table; if no target member node exists in the local routing table, or if the last active time of a member node exceeds a preset time threshold T. timeout If the target member node exists in the local routing table, it indicates that the link is connected. If the central node is in a disconnected or lost link state, it enters global discovery mode, specifically as follows: The central node generates a set of orthogonal beam weight vectors W={w} through an FPGA beam scanning controller. 1, w2,...,w M }; where M is the total number of beams required for omnidirectional coverage; The central node controls the phase shifter of the radio frequency front end to quickly poll the M beam directions in the order of the orthogonal beam weight vector set W during the reception period of each network maintenance frame in order to capture network maintenance frames from any spatial direction. If the link is connected, the central node will receive the latest angle information θ from the network maintenance frame of the target member node. curr Update the local routing table, set the system status flag to connected, and enter local tracing mode, specifically: In the next network maintenance frame reception cycle, the central node reads the previous historical angle information θ of the target member node from its local routing table. last ; Instead of traversing all beams in the orthogonal beam weight vector set W, the FPGA beam scanning controller generates a local neighborhood subset of beams. The local neighborhood beam subset Including historical angle θ last The beam scanning range is limited to the K beams to its left and right, and the K beams adjacent to it. Within the interval; where, For a single beam, 3dB width This is the preset tracking window coefficient.

4. A single-point location network maintenance method for distributed cooperative communication according to claim 1, characterized in that: In step 2, the central node demodulates the digital baseband signal and performs protocol parsing to obtain network layer information, specifically including: Time-frequency synchronization and channel equalization processing are performed on digital baseband signals; The digital baseband signal, after time-frequency synchronization and channel equalization processing, is decoded according to the preset encoding rules to obtain the information bit sequence; The central node parses the network layer information from the information bit sequence.

5. A single-point location network maintenance method for distributed cooperative communication according to claim 1, characterized in that: Step 2, which involves synchronously extracting the physical layer channel features and timing features of the digital baseband signal from the network maintenance frame, specifically includes: The central node extracts physical layer channel features, including signal-to-noise ratio (SNR) and beam index, from the network maintenance frame: During the preamble stage of receiving the network maintenance frame, the central node uses its internal energy detector to calculate the SNR in real time within the current received beam. dB During beam scanning, the central node maintains a set of registers to store the maximum signal-to-noise ratio (SNR). max and its corresponding beam index ID max Second largest signal-to-noise ratio (SNR) sec and its corresponding beam index ID sec ; The central node extracts timing features, including synchronization pulses, from the digital baseband signal: the central node compares the digital baseband signal with the locally pre-stored standard synchronization word sequence. Perform cross-correlation calculations to obtain the cross-correlation peak value. The modulus of the cross-correlation peak value monitored by the central node | |, if the modulus| |Exceeding the preset judgment threshold At this point, the central node determines that synchronization is successful and generates a synchronization pulse. .

6. A single-point location network maintenance method for distributed cooperative communication according to claim 1 or 5, characterized in that: Step 3 specifically includes: Step 3.1: The central node reads the registered maximum signal-to-noise ratio (SNR) in the logarithmic domain. max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain sec Then, the maximum signal-to-noise ratio (SNR) in the logarithmic domain is obtained by using the exponential transformation formula. max With the second largest signal-to-noise ratio (SNR) in the logarithmic domain sec Convert to the maximum signal-to-noise ratio (SNRmax_line) and the second-largest signal-to-noise ratio (SNRsec_line) in the linear domain; the correlation index conversion formula is: Step 3.2: Calculate the energy ratio factor η based on the maximum signal-to-noise ratio (SNRmax_line) in the linear domain and the second-largest signal-to-noise ratio (SNRsec_line) in the linear domain; the relevant calculation formula is as follows: Step 3.3: The central node reads the registered beam index ID. max With beam index ID sec Compare beam index IDs max With beam index ID sec The relative position is used to determine the interpolation direction. :like If the secondary strong signal is located to the left of the main beam, it is marked. ;like If the secondary strong signal is located to the right of the main beam, it is marked. ; Step 3.4: The central node uses the energy ratio factor η as the index address to query its internally stored fine-tuning mapping table and outputs the corresponding angle deviation. ; Step 3.5: The central node is based on the beam index ID. max Interpolation direction , angle deviation Calculate the angle of arrival (AOA); the relevant calculation formula is as follows: in, Beam Index ID max The corresponding physical center pointing angle.

7. A single-point location network maintenance method for distributed cooperative communication according to claim 1 or 5, characterized in that: Step 4 specifically includes: Step 4.1: The central node monitors the physical state of the current receiving beam in real time, and sets the positioning gate signal Gate_En to an active level only when both decision conditions are met simultaneously; Step 4.2: Match the positioning gate signal Gate_En with the synchronization pulse of the timing characteristics. Perform an AND operation to obtain the system-defined trigger signal. The relevant calculation expression is: Step 4.3: The FPGA of the central node maintains a counter with a counting frequency of f. clk When the system defines a trigger signal When a rising edge is detected, the current count value T of the counter is... cnt It was instantly latched into the TOA data register; Step 4.4: The central node performs delay compensation on the arrival time (TOA) latched in the TOA data register; the relevant calculation expression is: in, This is the hardware group latency compensation value.

8. A single-point location network maintenance method for distributed cooperative communication according to claim 7, characterized in that: The two decision conditions in step 4.1 include the signal-to-noise ratio (SNR) condition and the direct beam path characteristic condition; the SNR condition is the currently detected beam SNR. It must be greater than the preset quality threshold. The direct beam characteristic condition is the currently detected beam temporal width. It must be smaller than the preset width threshold. .

9. A single-point location network maintenance method for distributed cooperative communication according to claim 1, characterized in that: Step 5 specifically includes: Step 5.1: The central node reads the angle of arrival. And arrival time (TOA), convert the arrival time (TOA) to distance. Then, the coordinates of the member nodes are calculated using the transformation formula from spherical coordinates to Cartesian coordinates. The transformation formula from the spherical coordinate system to the Cartesian coordinate system is as follows: in, At the speed of light, It is the azimuth angle. Angle of elevation; Step 5.2: The central node calculates the coordinates of the member nodes. Update the local routing table and construct a topology response frame, using network layer information to specify the coordinates of member nodes. Encapsulated in the data payload, the topology response frame is sent back to the member node in the next communication time slot; Step 5.3: After receiving the topology response frame, the member node parses the topology response frame to obtain its own position relative to the central node. Based on its own position relative to the central node, the member node performs formation maintenance, path planning, or transmission power adjustment to complete network maintenance.

10. A single-point location network maintenance system for distributed cooperative communication, characterized in that: include: Adaptive beam scanning and signaling capture module: The central node adaptively adjusts the beam scanning strategy according to the routing status, captures the network maintenance frames sent by member nodes in global discovery or local tracking mode, and converts the network maintenance frames into digital baseband signals; Parallel extraction module for communication sensing features: The central node demodulates and parses the digital baseband signal to obtain network layer information, and simultaneously extracts the physical layer channel features of the network maintenance frame and the timing features of the digital baseband signal; Angle of Arrival (AOA) Module: Based on the physical layer channel characteristics of the network maintenance frame, the module calculates the angle deviation exceeding the physical beam resolution using an interpolation algorithm to obtain the AOA. Hardware-gated arrival time latch module: Based on the timing characteristics of the digital baseband signal, it triggers a hardware latching action together with the positioning gating signal to obtain the arrival time (TOA). Location calculation and topology closed-loop maintenance module: The central node calculates the location information of member nodes by combining the angle of arrival (AOA) and time of arrival (TOA), and then feeds back the location information and network layer information to the member nodes to complete network maintenance.

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