Integrated system for sensing and perception, index determination method, electronic device and medium

Abstract

The application provides a sensing integrated fusion system, an index determination method, an electronic device and a medium, relates to the technical field of communication, and the sensing integrated fusion system comprises a fusion base station, a preset terminal and a fusion server. The fusion base station is provided with a passive Internet of Things module, and the preset terminal is provided with an RFID tag. The fusion base station is used for sending a first signal and receiving a second signal through the passive Internet of Things module. The first signal comprises a first sensing signal and an RFID excitation signal. The RFID excitation signal multiplexes the waveform and time slot resources of the first sensing signal. The second signal comprises a second sensing signal obtained by reflecting the first sensing signal through the preset terminal and an RFID uplink signal obtained by backscattering the RFID excitation signal through the RFID tag. The fusion server is used for performing fusion calculation according to the received second sensing signal and RFID uplink signal to determine a sensing performance index. The sensing performance of the system can be more comprehensively and accurately evaluated, and the accuracy of the sensing performance index is improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a fusion system of communication and sensing, a method for determining indicators, an electronic device, and a medium. Background Technology

[0002] The sensing efficiency of this technology is built upon specialized sensing hardware. By analyzing physical phenomena such as radio wave reflection and scattering, it can accurately acquire distance, angle, and velocity parameters of moving targets and their environment. Based on this data, the technology can achieve functions such as localization, identification, tracking, and environmental reconstruction, and is widely used in various fields.

[0003] Noise exists between the external environment and the receiver, which can interfere with radio wave analysis, leading to deviations in ranging, angle measurement, and velocity measurement of moving targets or environmental information, and consequently, false alarms or missed detections. Currently, the calculation of perception performance indicators (such as false alarm rate and missed detection rate) is generally performed in a controlled testing environment. However, real-world application scenarios are complex and varied, differing from testing environments, making it difficult to comprehensively and accurately assess actual conditions using perception performance indicators calculated during the testing phase.

[0004] It is evident that the perception performance indicators determined in the existing technology have poor accuracy. Summary of the Invention

[0005] This application provides a sensory integration system, an index determination method, an electronic device, and a medium to address the problem of poor accuracy in the determination of sensing performance indicators in the prior art.

[0006] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, embodiments of this application provide a fusion system integrating sensing and communication, comprising: a fusion base station, a preset terminal, and a fusion server. The fusion base station is equipped with a passive IoT module, and the fusion base station is communicatively connected to the fusion server through the passive IoT module. The preset terminal is equipped with a radio frequency identification (RFID) tag. The fusion base station is used to send a first signal and receive a second signal through the passive IoT module. The first signal includes a first sensing signal and an RFID excitation signal. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal. The second signal includes a second sensing signal after the first sensing signal is reflected by the preset terminal and an RFID uplink signal after the RFID excitation signal is backscattered by the RFID tag. The fusion server is used to perform fusion calculations based on the received second sensing signal and the RFID uplink signal to determine sensing performance indicators.

[0007] Optionally, the sensor-integrated fusion system also includes: The sensing network element SF server, the passive IoT module communicates with the fusion server through the SF server, and the SF server is used to forward and manage the second signal in the passive IoT module; When the fusion server receives the second signal forwarded by the SF server, it determines a set of sensing angles based on the second sensing signal and a set of angles of arrival based on the RFID uplink signal; and determines the sensing performance indicators based on the matching relationship between the set of sensing angles and the set of angles of arrival. The sensing performance indicators include false alarm rate and missed detection rate.

[0008] Optionally, the integrated sensing and communication system further includes: a first baseband unit and a second baseband unit, wherein one first baseband unit is communicatively connected to one of the integrated base stations, and one or more first baseband units are communicatively connected to the second baseband unit. The first baseband unit is used to store the signal received by the passive IoT module, and the second baseband unit is used to send the second signal obtained by deduplicating the signal stored in the first baseband unit to the integrated server.

[0009] Secondly, this application provides an indicator determination method applied to a sensor-integrated fusion system. The sensor-integrated fusion system includes: a fusion base station, a preset terminal, and a fusion server. The fusion base station is equipped with a passive IoT module and is communicatively connected to the fusion server through the passive IoT module. The preset terminal is equipped with an RFID tag. The method includes: The fusion base station sends a first signal to the preset terminal. The first signal includes a first sensing signal and an RFID excitation signal. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal. The fusion base station receives a second signal through the passive IoT module. The second signal includes a second sensing signal after the first sensing signal is reflected by the preset terminal and an RFID uplink signal after the RFID excitation signal is backscattered by the RFID tag. The fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine the sensing performance indicators.

[0010] Optionally, the integrated sensing system further includes an SF server, and the passive IoT module communicates with the fusion server through the SF server; The fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine sensing performance indicators, including: The fusion base station sends the second sensing signal and the RFID uplink signal to the fusion server through the SF server; The fusion server determines a set of sensing angles based on the second sensing signal and a set of arrival angles based on the RFID uplink signal. The sensing angles in the set of sensing angles represent the angles of the preset terminal relative to the fusion base station, and the arrival angles in the set of arrival angles represent the angles at which the RFID uplink signal reaches the fusion base station. The fusion server determines the perception performance indicators based on the matching relationship between the set of perception angles and the set of arrival angles.

[0011] Optionally, the fusion server determines perception performance indicators based on the matching relationship between the set of perception angles and the set of angles of arrival, including: The fusion server determines the false alarm rate based on the number of target sensing angles in the set of sensing angles and the sum of the number of target sensing angles and the total number of angles of arrival in the set of angles of arrival. The error value between the target sensing angle and any angle of arrival in the set of angles of arrival is greater than a first threshold. The fusion server determines the false alarm rate based on the number of target angles of arrival in the set of angles of arrival and the total number of angles of arrival in the set of angles of arrival. The error between the target angle of arrival and any sensing angle in the set of sensing angles is greater than a second threshold. The sensing performance indicators include the false alarm rate and the false alarm rate.

[0012] Optionally, after the fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine the sensing performance indicators, the method further includes: If the perception performance index does not meet the preset index range, the fusion server determines the first half-power angle of the desired beam in the horizontal plane and the second half-power angle of the desired beam in the vertical plane based on the set of angles of arrival. The set of angles of arrival is determined based on the RFID uplink signal at the first moment. The fusion server sends the beam parameters at the second moment to the fusion base station. The beam parameters at the second moment are determined based on the first half-power angle and the second half-power angle. The second moment is a moment after the first moment. At the second moment, the fusion base station sends a third signal according to the beam parameters, the third signal including a third sensing signal and an RFID excitation signal adjusted based on the beam parameters.

[0013] Optionally, the beam parameters include the number of horizontal triggering elements and the number of vertical triggering elements, which are determined according to the following formula: ; ; In the formula, N x The number of horizontally triggered oscillators. N y The number of trigger oscillators in the vertical direction. k x and k y λ is a constant, and λ is the wavelength of the working electromagnetic wave. D x The physical aperture of the array in the horizontal direction. D y The physical aperture of the array in the vertical direction. d x Let be the spacing of the oscillators in the horizontal direction. d y Let be the spacing of the oscillators in the vertical direction. i HPBx For the first half-power angle, i HPBy This is the second half-power angle.

[0014] Thirdly, embodiments of this application provide an electronic device, including: a processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, it implements the steps of the index determination method as described in the first aspect.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the index determination method as described in the first aspect.

[0016] In this embodiment, by analyzing the second sensing signal after the first sensing signal is reflected by a preset terminal, ranging, angle measurement, and speed measurement of the preset terminal can be achieved, thereby realizing functions such as positioning, identification, tracking, and environmental reconstruction. An RFID tag is attached to the preset terminal, and the RFID uplink signal returned by the RFID tag after the RFID excitation signal is analyzed to determine the benchmark value for subsequent fusion analysis. Furthermore, the RFID excitation signal reuses the waveform and time slot resources of the first sensing signal, achieving efficient resource utilization. A passive IoT module is integrated into the fusion base station, and by adjusting the receiving window strategy, it is ensured that the window can simultaneously receive and process RFID signals and sensing signals. Thus, the fusion server performs fusion calculations based on the second sensing signal and the RFID uplink signal to determine sensing performance indicators. By comprehensively utilizing information from different signals, the sensing performance of the system is evaluated more comprehensively and accurately, improving the accuracy of sensing performance indicators. This provides strong support for system performance optimization and application scenario adaptation, enhancing the system's adaptability and reliability in complex environments. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the structure of a sensory integration system provided in an embodiment of this application; Figure 2 This is one of the flowcharts of an indicator determination method provided in the embodiments of this application; Figure 3 This is the second flowchart of an indicator determination method provided in the embodiments of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0021] This application provides a sensory integration system, such as Figure 1 As shown, it includes: a converged base station, a preset terminal, and a converged server. The converged base station adds a passive IoT module to the sensing module, and the converged base station communicates with the converged server through the passive IoT module. The preset terminal is equipped with a Radio Frequency Identification (RFID) tag; wherein, The fusion base station can send a first signal through the sensing module and receive a second signal through the passive IoT module. The first signal includes a first sensing signal and an RFID excitation signal. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal. The second signal includes a second sensing signal after the first sensing signal is reflected by the preset terminal and an RFID uplink signal after the RFID excitation signal is backscattered by the RFID tag. The fusion server is used to perform fusion calculations based on the received second sensing signal and the RFID uplink signal to determine sensing performance indicators.

[0022] In this embodiment, the first sensing signal sent by the fusion base station can be a sensing signal generated based on sensing technology, possessing physical characteristics such as reflection and scattering. By analyzing the second sensing signal after the first sensing signal is reflected by a preset terminal, ranging, angle measurement, and velocity measurement of the preset terminal or environmental information can be achieved, thereby realizing functions such as positioning, identification, tracking, and environmental reconstruction. The preset terminal can be a terminal device such as a drone. Furthermore, an RFID tag is attached to the preset terminal, and the RFID uplink signal returned by the RFID tag after the RFID excitation signal is analyzed to determine the benchmark value for subsequent fusion analysis. Moreover, the RFID excitation signal reuses the waveform and time slot resources of the first sensing signal, achieving efficient resource utilization. A passive IoT module is integrated into the fusion base station, and by adjusting the receiving window strategy, it is ensured that the window can simultaneously receive and process RFID signals and sensing signals.

[0023] In this way, the fusion server performs fusion calculations based on the second sensing signal and the RFID uplink signal to determine the sensing performance indicators. By comprehensively utilizing the information from different signals, it can more comprehensively and accurately evaluate the sensing performance of the system, improve the accuracy of the sensing performance indicators, provide strong support for system performance optimization and application scenario adaptation, and enhance the system's adaptability and reliability in complex environments.

[0024] Optionally, the sensor-integrated fusion system also includes: The Sensing Function (SF) server is used to forward and manage the second signal in the passive IoT module. The passive IoT module is connected to the fusion server through the SF server. When the fusion server receives the second signal forwarded by the SF server, it determines a set of sensing angles based on the second sensing signal and a set of angles of arrival (AoA) based on the RFID uplink signal; and determines the sensing performance indicators based on the matching relationship between the set of sensing angles and the set of angles of arrival, the sensing performance indicators including false alarm rate and missed detection rate.

[0025] In this embodiment, the integrated sensing system can adopt a loosely coupled architecture. The SF server is deployed on the wireless access side, allowing the passive IoT module to communicate with the fusion server through the SF server. After the SF server forwards the second signal (i.e., the second sensing signal and the RFID uplink signal), the fusion server performs fusion calculations to ultimately calculate the false alarm rate and missed detection rate, improving the accuracy of the determined sensing performance indicators and achieving precise evaluation of the sensing system's detection performance. Furthermore, the SF server can also communicate with the application platform to forward and report information. The application platform can adjust the user interface display or trigger specific business logic based on the sensing performance indicators.

[0026] Specifically, after receiving the second information forwarded by the SF server, the fusion server processes the sensor echo signal (i.e., the second sensing signal) to extract parameters such as the orientation and distance of the preset terminals, generating a set of sensing angles. Simultaneously, the fusion server processes the backscattered signal from the RFID tags (i.e., the RFID uplink signal) to analyze precise location information based on the tag's line-of-sight propagation characteristics, generating a set of angles of arrival. Further, by comparing the set of sensing angles with the set of angles of arrival, signals sensed but without tag verification are determined as false alarms, and signals with tags present but not sensed are determined as missed detections. Since RFID signal transmission and reception both propagate along a line-of-sight (LOS) path, they can efficiently and accurately capture information from all preset terminals carrying RFID tags. Therefore, in this embodiment, the false alarm rate and missed detection rate are calculated based on the set of angles of arrival of the RFID uplink signal, improving the accuracy of the determined sensing performance indicators.

[0027] In one embodiment, any angle of arrival in the set of angles of arrival is determined based on the RFID uplink signal. i Please refer to the following formula: ; ; in, d The distance between the two oscillators is the distance at which the signal reaches. The phase difference between the arrival of the signal and the two oscillators. i Angle of arrival.

[0028] Furthermore, by setting an error threshold, within the error range, it can be determined whether there is a record in the set of perceived angles that matches the angle of arrival in the set of angles of arrival. If it exists, it is considered that the preset terminal corresponding to the RFID tag has been sensed by the fusion base station; if it does not exist, it is considered that the preset terminal corresponding to the RFID tag has not been sensed, and a missed detection occurs. The formula for calculating the missed detection rate can be found below: ; ; in, For any angle of arrival in the set of angles of arrival, that is, the angle of arrival corresponding to the RFID uplink signal backscattered by the RFID tag on any preset terminal, i 2 represents the set of perception angles. The preset error threshold, This indicates the number of missed detections (i.e., the number of target arrival angles). n The total number of angles of arrival in the angles of arrival set (i.e., the number of trusted pre-defined terminals, or the number of RFID tags). R 1 represents the false negative rate.

[0029] Similarly, by setting an error threshold, within the error range, it can be determined whether there exists a record in the set of angles of arrival that matches the angle of arrival in the set of angles of perception. If the angle of arrival sensed by the fused base station exists in the set of angles of arrival, there is no false alarm; if the angle of arrival sensed by the fused base station does not exist in the set of angles of arrival, a false alarm occurs. The formula for calculating the false alarm rate can be found below: ; ; in, For any one of the set of perception angles i 1 represents the set of arrival angles. This indicates the number of false alarms (i.e., the number of target perception angles). n The total number of angles of arrival in the angles of arrival set (i.e., the number of trusted pre-defined terminals, or the number of RFID tags). This represents the sum of the number of target sensing angles (i.e., the number of false alarms) and the total number of angles of arrival in the set of angles of arrival (i.e., the number of RFID tags). R 2 represents the false alarm rate.

[0030] In this way, the fusion server performs fusion calculations based on the set of sensing angles corresponding to the second sensing signal and the set of arrival angles corresponding to the RFID uplink signal to determine the sensing performance indicators. This provides a true reflection of the false alarm and missed detection rates in complex environments under different scenarios. By comprehensively utilizing information from different signals, the system's sensing performance is evaluated more comprehensively and accurately, improving the accuracy of sensing performance indicators. This provides strong support for system performance optimization and application scenario adaptation, enhancing the system's adaptability and reliability in complex environments.

[0031] Optionally, the integrated sensing and communication system further includes: a first baseband unit and a second baseband unit, wherein one first baseband unit is communicatively connected to one of the integrated base stations, and one or more first baseband units are communicatively connected to the second baseband unit. The first baseband unit is used to store the signal received by the passive IoT module, and the second baseband unit is used to send the second signal obtained by deduplicating the signal stored in the first baseband unit to the integrated server.

[0032] In this embodiment, the first baseband unit can be a slave baseband unit, and the second baseband unit can be a master baseband unit. The first baseband unit is directly connected to the fusion base station and is responsible for storing the raw signals (including mixed data such as the second sensing signal and RFID uplink signal) received by the passive IoT module in real time. This provides a complete signal record for subsequent processing, ensuring that the raw data is not lost and facilitating backtracking verification or in-depth analysis. The second baseband unit integrates the stored signals of one or more first baseband units and extracts the unique and valid second signal (i.e., the target sensing signal and the RFID reflection signal) through deduplication processing (such as removing duplicate samples of the same signal, eliminating redundant copies caused by multipath transmission, and merging signals of the same source and frequency). This avoids duplicate data occupying transmission bandwidth and computing resources, improving signal processing efficiency. In this way, the deduplicated signal more accurately reflects the signal characteristics in the real scene (such as parameters such as angle of arrival and sensing angle), reduces calculation errors caused by data redundancy, and ensures that the fusion server performs angle matching and performance index calculation (such as false alarm rate and missed detection rate) based on valid data, thereby optimizing the sensing accuracy and resource utilization efficiency of the integrated sensing system.

[0033] Through the collaboration of two-level baseband units, the system achieves layered processing from raw signal acquisition and redundancy filtering to effective data transmission. While ensuring data integrity, it reduces the complexity and resource consumption of subsequent fusion calculations, laying the foundation for high-precision sensing and communication fusion.

[0034] See Figure 2 , Figure 2 This is one of the flowcharts for an indicator determination method provided in an embodiment of this application, applied to a sensor-integrated fusion system. The sensor-integrated fusion system includes: a fusion base station, a preset terminal, and a fusion server. The fusion base station is equipped with a passive IoT module, and the fusion base station is communicatively connected to the fusion server through the passive IoT module. The preset terminal is equipped with an RFID tag. Figure 2 As shown, the method includes the following steps: Step 201: The fusion base station sends a first signal to the preset terminal. The first signal includes a first sensing signal and an RFID excitation signal. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal. In this step, by analyzing the second sensing signal after the first sensing signal is reflected by a preset terminal, ranging, angle measurement, and velocity measurement of the preset terminal or environmental information can be achieved, thereby realizing functions such as positioning, identification, tracking, and environmental reconstruction. An RFID tag is attached to the preset terminal, and the RFID uplink signal returned by the RFID tag after the RFID excitation signal is analyzed to determine the benchmark value for subsequent fusion analysis. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal; that is, the same signal sent by the base station has both sensing detection and RFID tag activation functions, avoiding redundancy from independently allocating signal resources, improving spectrum and time resource utilization, reducing system complexity and energy consumption, and realizing the high efficiency of integrated sensing technology in resource utilization.

[0035] Step 202: The fusion base station receives a second signal through the passive IoT module. The second signal includes a second sensing signal after the first sensing signal is reflected by the preset terminal and an RFID uplink signal after the RFID excitation signal is backscattered by the RFID tag. In this step, a passive IoT module is integrated into the fusion base station. This passive IoT module must be capable of processing two types of signals simultaneously. By adjusting the receiving window strategy and optimizing the signal processing link, the synchronous reception and separation of the two types of signals are ensured, providing raw data for subsequent analysis. The echo signal formed by the reflection of the first sensing signal after being sent to the preset terminal (i.e., the second sensing signal) carries environmental and motion information such as the distance, speed, and angle of the preset terminal, forming the basis for the sensing system to achieve target detection and positioning. After the RFID excitation signal activates the tag, the tag returns the RFID uplink signal through backscatter modulation. This signal contains the tag's unique identifier, location, and other information, exhibiting line-of-sight propagation characteristics, and can accurately confirm the presence and status of the preset terminal.

[0036] Step 203: The fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine the sensing performance indicators.

[0037] In this step, the fusion server performs fusion calculations based on the second sensing signal and the RFID uplink signal to determine the sensing performance indicators. By comprehensively utilizing the information from different signals, it can more comprehensively and accurately evaluate the sensing performance of the system, improve the accuracy of the sensing performance indicators, provide strong support for system performance optimization and application scenario adaptation, and enhance the system's adaptability and reliability in complex environments.

[0038] This application provides a method for determining indicators in a fusion system of sensing and communication. Based on the fusion system of sensing and communication, a complete closed loop from signal transmission and acquisition to analysis is realized. Sensing signals and RFID are deeply integrated. The precise identification characteristics of RFID tags make up for the deficiencies of sensing detection, improve the accuracy of sensing performance indicators, and thus improve the sensing performance of the system in complex scenarios.

[0039] Optionally, the integrated sensing system further includes an SF server, and the passive IoT module communicates with the fusion server through the SF server; The fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine sensing performance indicators, including: The fusion base station sends the second sensing signal and the RFID uplink signal to the fusion server through the SF server; The fusion server determines a set of sensing angles based on the second sensing signal and a set of arrival angles based on the RFID uplink signal. The sensing angles in the set of sensing angles represent the angles of the preset terminal relative to the fusion base station, and the arrival angles in the set of arrival angles represent the angles at which the RFID uplink signal reaches the fusion base station. The fusion server determines the perception performance indicators based on the matching relationship between the set of perception angles and the set of arrival angles.

[0040] In this embodiment, after receiving the second information forwarded by the SF server, the fusion server processes the sensor echo signal (i.e., the second sensing signal) to extract parameters such as the orientation and distance of the preset terminal to generate a set of sensing angles. Simultaneously, the fusion server processes the backscattered signal from the RFID tag (i.e., the RFID uplink signal) to generate a set of arrival angles based on the tag's line-of-sight propagation characteristics and precise location information. Furthermore, the fusion server compares the set of sensing angles with the set of arrival angles: signals sensed but without tag verification are determined as false alarms, and signals with tags present but not sensed are determined as missed detections. Since RFID signal transmission and reception both propagate along the LOS path, they can efficiently and accurately capture information from all preset terminals carrying RFID tags. Therefore, in this embodiment, the set of arrival angles of the RFID uplink signal is used as a benchmark, and the sensing performance index is calculated based on the matching relationship between the set of sensing angles and the set of arrival angles, improving the accuracy of the determined sensing performance index.

[0041] The integration of communication and sensing, as a key technological innovation, not only retains the integrity of traditional communication functions but also significantly expands system capabilities, including sensing and identification. This technology is widely used in low-altitude applications to sense the activities of pre-positioned terminals (such as drones). Its sensing performance indicators mainly include false alarm rate and false negative rate. The false alarm rate and false negative rate are affected by noise between the external environment and the receiver, and their levels directly relate to the stability and security of operational services. Based on this, the specific sensing performance indicators can be defined as follows: Optionally, the fusion server determines perception performance indicators based on the matching relationship between the set of perception angles and the set of angles of arrival, including: The fusion server determines the false alarm rate based on the number of target sensing angles in the set of sensing angles and the sum of the number of target sensing angles and the total number of angles of arrival in the set of angles of arrival. The error value between the target sensing angle and any angle of arrival in the set of angles of arrival is greater than a first threshold. The fusion server determines the false alarm rate based on the number of target angles of arrival in the set of angles of arrival and the total number of angles of arrival in the set of angles of arrival. The error between the target angle of arrival and any sensing angle in the set of sensing angles is greater than a second threshold. The sensing performance indicators include the false alarm rate and the false alarm rate.

[0042] For example, the target sensing angle can be a sensing angle in the sensing angle set that does not match any of the arrival angles (i.e., the error value is greater than the first threshold). Such sensing angles have no corresponding existence in the arrival angle set of the RFID uplink signal and are judged as false alarms. For example, the sensing angle set includes 3 angles (θ1=15°, θ2=30°, θ3=45°), but the arrival angle set only includes θ2 of these three angles. Then θ1 and θ3 are the target sensing angles (assuming the first threshold is ±5°).

[0043] The target angle of arrival can be an angle of arrival in the set of angles of arrival that does not match any of the sensing angles (i.e., the error value is greater than the second threshold). Such angles of arrival have no corresponding existence in the set of sensing angles of the second sensing signal and are judged as missed detections. For example, the set of angles of arrival includes two angles (φ1=20°, φ2=50°), but the set of sensing angles only includes φ1. Then φ2 is the target angle of arrival (assuming the second threshold is ±5°).

[0044] In this way, by fusing the set of sensing angles corresponding to the second sensing signal and the set of arrival angles corresponding to the RFID uplink signal, the sensing performance indicators are determined, which can accurately reflect the false alarm and missed detection rates in different complex environments. By comprehensively utilizing information from different signals, the system's sensing performance can be evaluated more comprehensively and accurately, improving the accuracy of sensing performance indicators. This provides strong support for system performance optimization and application scenario adaptation, and enhances the system's adaptability and reliability in complex environments.

[0045] In some optional embodiments, after the fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine the sensing performance indicators, the method further includes: If the perception performance index does not meet the preset index range, the fusion server determines the first half-power angle of the desired beam in the horizontal plane and the second half-power angle of the desired beam in the vertical plane based on the set of angles of arrival. The set of angles of arrival is determined based on the RFID uplink signal at the first moment. The fusion server sends the beam parameters at the second moment to the fusion base station. The beam parameters at the second moment are determined based on the first half-power angle and the second half-power angle. The second moment is a moment after the first moment. At the second moment, the fusion base station sends a third signal according to the beam parameters, the third signal including a third sensing signal and an RFID excitation signal adjusted based on the beam parameters.

[0046] In this embodiment, as Figure 3 As shown, firstly, the fusion base station inventory sensing function is activated, and a first signal is sent to a preset terminal. The first signal includes a first sensing signal and an RFID excitation signal. Then, a set of sensing angles is determined based on a second sensing signal, and a set of arrival angles is determined based on the RFID uplink signal. The second sensing signal is the signal after the first sensing signal is reflected by the preset terminal, and the RFID uplink signal is the signal after the RFID excitation signal is backscattered by the RFID tag. Based on the set of arrival angles and the set of sensing angles, the false alarm rate and the missed detection rate are calculated. This can be achieved by the fusion server determining the false alarm rate based on the number of target sensing angles in the set of sensing angles and the sum of the number of target sensing angles and the total number of arrival angles in the set of arrival angles. The missed detection rate is determined by the fusion server based on the number of target arrival angles in the set of arrival angles and the total number of arrival angles in the set of arrival angles. Then, if the sensing performance indicators (i.e., the false alarm rate and the missed detection rate) do not meet the preset indicator range, the sensing performance indicators are optimized, as described in the following description: The fusion server determines the first half-power angle of the desired beam in the horizontal plane and the second half-power angle of the desired beam in the vertical plane based on the set of angles of arrival. In other words, it measures the direction of the angle of arrival of the RFID uplink signal backscattered by the RFID tag using the uplink angle of arrival (UL-AOA) technology to obtain the set of angles of arrival. This allows the calculation of the upper and lower limits of the angles of arrival in the horizontal and vertical planes, and thus the acquisition of the first half-power angle of the desired beam in the horizontal plane and the second half-power angle of the desired beam in the vertical plane. Then, beam parameters are calculated, including the relative offset of the antenna elements required for the beam, the number of horizontal trigger elements, and the number of vertical trigger elements. After obtaining the beam parameters, the fusion server sends them to the fusion base station to configure the required beam. The fusion base station sends a third signal based on the beam parameters, which includes a third sensing signal adjusted based on the beam parameters and an RFID excitation signal, i.e., the fusion base station re-senses. Finally, the beam-optimized sensing results are generated, and the false alarm rate and missed detection rate are recalculated. By dynamically optimizing the beam coverage and direction, the signal energy in the target area is enhanced in a targeted manner, and interference in non-target areas is suppressed, thereby improving the accuracy of subsequent sensory perception and RFID tag identification, reducing the false alarm rate and missed detection rate, and optimizing the sensing performance indicators.

[0047] For example, at time t=1, the sensing beam (i.e., the second sensing signal reflected back from the preset terminal via the first sensing signal) senses the preset terminal for the first time. At the same time, the RFID system completes the inventory of all RFID tags and sets the angle of arrival of the RFID uplink signals. i 3. Upload to the fusion server and decompose into a set of horizontal plane arrival angles. i 3x and the set of vertical plane arrival angles i 3y The fusion server analyzes this data to determine the first half-power angle of the desired beam on the horizontal plane. i HPBx And the second half-power angle of the desired beam in the vertical plane i HPBy Among them, the first half-power angle i HPBx and the second half-power angle of the desired beam in the vertical plane i HPBy It can be expressed as the following formula: ; .

[0048] At time t=2, based on the newly set beam parameters of the fusion base station, a narrower, higher-gain beam is transmitted, and sensing is re-performed to obtain updated sensing results. The phase shift of each element is calculated based on the array's geometry, such as element spacing and array size, and the desired beam pointing azimuth and tilt angles. These phase shifts ensure that constructive interference can occur in the beam pointing direction when the radiation fields of the elements are superimposed in space.

[0049] Optionally, the relative offset of the antenna elements in the beam parameters can be calculated using the following formula: ; ; in, The phase difference between each oscillator in a Uniform Planar Array (UPA) and a reference array, including the horizontal phase difference. and vertical phase difference , d x and d y These are the horizontal and vertical spacings of the oscillator, respectively. m 0 ，n 0 () is the reference oscillator position. i It is the tilt angle of the UPA antenna. It is the azimuth angle of the UPA antenna. l It is the wavelength of the working electromagnetic wave.

[0050] Optionally, a beam with specific gain and horizontal and vertical width can be formed by adjusting the number of triggering elements in the horizontal and vertical directions. The number of triggering elements in the horizontal and vertical directions is determined according to the following formula: ; ; In the formula, N x The number of horizontally triggered oscillators. N y The number of trigger oscillators in the vertical direction. k x and k y λ is a constant, and λ is the wavelength of the working electromagnetic wave. D x The physical aperture of the array in the horizontal direction. D y The physical aperture of the array in the vertical direction. d xLet be the spacing of the oscillators in the horizontal direction. d y Let be the spacing of the oscillators in the vertical direction. i HPBx For the first half-power angle, i HPBy This is the second half-power angle.

[0051] At time t=3, RFID inventory and sensing are performed again to capture any dynamic changes. At time t=4, the operation at t=2 is repeated to continuously optimize beam alignment and gain. Through the above cycle, at even-numbered times, the beam gain is significantly enhanced, the signal strength is improved, and thus the signal-to-noise ratio (SNR) is increased, effectively reducing the false alarm rate and missed detection rate.

[0052] In this way, after determining that the perception performance indicators (such as false alarm rate and false negative rate) do not meet the preset standards, the fusion server calculates the half-power angle of the desired beam in the horizontal and vertical directions based on the accurate angle of arrival set of the RFID uplink signal at the first moment, and generates the beam parameters for the second moment accordingly, and sends them to the fusion base station. The base station sends the adjusted third signal according to the new parameters at the second moment. By dynamically optimizing the beam coverage and direction, the signal energy of the target area is enhanced in a targeted manner, and interference in non-target areas is suppressed, thereby improving the accuracy of subsequent sensory perception and RFID tag identification, reducing the false alarm rate and false negative rate, and realizing the optimization of perception performance indicators.

[0053] This application also provides an electronic device, including: a processor, a memory, and a program stored in the memory and executable on the processor. When the program is executed by the processor, it implements the various processes of the above-described indicator determination method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0054] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements the various processes of the above-described indicator determination method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0055] This application also provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, they implement the various processes of the above-described indicator determination method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0056] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0057] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0058] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A synergistic sensing integrated system, characterized in that, include: The system integrates a base station, a pre-set terminal, and a converged server. The integrated base station is equipped with a passive IoT module and communicates with the converged server through the passive IoT module. The pre-set terminal is equipped with a radio frequency identification (RFID) tag. The fusion base station is used to send a first signal and receive a second signal through the passive IoT module. The first signal includes a first sensing signal and an RFID excitation signal. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal. The second signal includes a second sensing signal after the first sensing signal is reflected by the preset terminal and an RFID uplink signal after the RFID excitation signal is backscattered by the RFID tag. The fusion server is used to perform fusion calculations based on the received second sensing signal and the RFID uplink signal to determine sensing performance indicators; The integrated sensing system also includes: The sensing network element SF server, the passive IoT module communicates with the fusion server through the SF server, and the SF server is used to forward and manage the second signal in the passive IoT module; When the fusion server receives the second signal forwarded by the SF server, it determines a set of sensing angles based on the second sensing signal and a set of angles of arrival based on the RFID uplink signal; and determines the sensing performance indicators based on the matching relationship between the set of sensing angles and the set of angles of arrival. The sensing performance indicators include false alarm rate and missed detection rate.

2. The sensor-integrated fusion system according to claim 1, characterized in that, Also includes: A first baseband unit and a second baseband unit, wherein one first baseband unit is communicatively connected to one of the fusion base stations, and one or more first baseband units are communicatively connected to the second baseband unit, wherein the first baseband unit is used to store the signal received by the passive IoT module, and the second baseband unit is used to send the second signal obtained by deduplicating the signal stored in the first baseband unit to the fusion server.

3. A method for determining an indicator, characterized in that, The system is applied to a sensor-integrated fusion system, which includes a fusion base station, a preset terminal, and a fusion server. The fusion base station is equipped with a passive IoT module and is communicatively connected to the fusion server through the passive IoT module. The preset terminal is equipped with an RFID tag. The method includes: The fusion base station sends a first signal to the preset terminal. The first signal includes a first sensing signal and an RFID excitation signal. The RFID excitation signal reuses the waveform and time slot resources of the first sensing signal. The fusion base station receives a second signal through the passive IoT module. The second signal includes a second sensing signal after the first sensing signal is reflected by the preset terminal and an RFID uplink signal after the RFID excitation signal is backscattered by the RFID tag. The fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine the sensing performance indicators; The integrated sensing system also includes an SF server, and the passive IoT module communicates with the fusion server through the SF server. The fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine sensing performance indicators, including: The fusion base station sends the second sensing signal and the RFID uplink signal to the fusion server through the SF server; The fusion server determines a set of sensing angles based on the second sensing signal and a set of arrival angles based on the RFID uplink signal. The sensing angles in the set of sensing angles represent the angles of the preset terminal relative to the fusion base station, and the arrival angles in the set of arrival angles represent the angles at which the RFID uplink signal reaches the fusion base station. The fusion server determines the perception performance indicators based on the matching relationship between the set of perception angles and the set of arrival angles.

4. The method according to claim 3, characterized in that, The fusion server determines perception performance indicators based on the matching relationship between the set of perception angles and the set of angles of arrival, including: The fusion server determines the false alarm rate based on the number of target sensing angles in the set of sensing angles and the sum of the number of target sensing angles and the total number of angles of arrival in the set of angles of arrival. The error value between the target sensing angle and any angle of arrival in the set of angles of arrival is greater than a first threshold. The fusion server determines the false alarm rate based on the number of target angles of arrival in the set of angles of arrival and the total number of angles of arrival in the set of angles of arrival. The error between the target angle of arrival and any sensing angle in the set of sensing angles is greater than a second threshold. The sensing performance indicators include the false alarm rate and the false alarm rate.

5. The method according to any one of claims 3 to 4, characterized in that, After the fusion server performs fusion calculations based on the second sensing signal obtained from the fusion base station and the RFID uplink signal to determine the sensing performance indicators, the method further includes: If the perception performance index does not meet the preset index range, the fusion server determines the first half-power angle of the desired beam in the horizontal plane and the second half-power angle of the desired beam in the vertical plane based on the set of angles of arrival. The set of angles of arrival is determined based on the RFID uplink signal at the first moment. The fusion server sends the beam parameters at the second moment to the fusion base station. The beam parameters at the second moment are determined based on the first half-power angle and the second half-power angle. The second moment is a moment after the first moment. At the second moment, the fusion base station sends a third signal according to the beam parameters, the third signal including a third sensing signal and an RFID excitation signal adjusted based on the beam parameters.

6. The method according to claim 5, characterized in that, The beam parameters include the number of horizontal triggering elements and the number of vertical triggering elements, which are determined according to the following formula: ； ； In the formula, N x The number of horizontally triggered oscillators. N y The number of trigger oscillators in the vertical direction. k x and k y λ is a constant, and λ is the wavelength of the working electromagnetic wave. D x The physical aperture of the array in the horizontal direction. D y The physical aperture of the array in the vertical direction. d x Let be the spacing of the oscillators in the horizontal direction. d y Let be the spacing of the oscillators in the vertical direction. θ HPBx For the first half-power angle, θ HPBy This is the second half-power angle.

7. An electronic device, characterized in that, include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the index determination method as described in any one of claims 3 to 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the index determination method as described in any one of claims 3 to 6.

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