A self-aware beamforming antenna system and method for outdoor cameras

Abstract

The application relates to the technical field of wireless communication and radio frequency antennas, and provides a self-sensing beamforming antenna system and method for an outdoor camera, which comprises the following modules: a reconfigurable antenna array module containing at least two antenna radiation units, each feeding point being connected with an independent adjustable matching network to regulate and control the phase / amplitude; a radio frequency tuning and control module containing an adjustable matching network and a driving circuit, the driving circuit receiving a digital control signal of a master decision unit and converting the signal into an analog voltage to be applied to a phase shifter; a channel sensing and processing module integrated in the camera, periodically acquiring and analyzing channel state information from a wireless router; and a master decision unit, which performs the whole process logic of scanning, calculation, locking and tracking, and automatically triggers re-optimization when the link degradation reaches a threshold. The application constructs a self-contained and self-sensing beamforming architecture on the camera side, realizes autonomous link optimization and dynamic beam regulation independent of network side devices, and improves the connection reliability.

Description

Technical Field

[0001] This application belongs to the field of wireless communication and radio frequency antenna technology, specifically relating to a self-sensing beamforming antenna system and method for outdoor cameras. Background Technology

[0002] Currently, in the fields of wireless communication and RF antenna technology, such as outdoor Wi-Fi security cameras, devices commonly employ 2.4G / 5G dual-band communication for video data transmission. Since outdoor cameras are typically fixed in locations such as eaves, exterior walls, or poles, while wireless routers are located indoors and in variable positions, signals need to penetrate walls for transmission. This results in significant path loss and environmental interference, easily leading to insufficient bandwidth, stuttering, high latency, and even disconnections. To improve transmission quality, existing technologies typically use omnidirectional antennas or fixed-angle directional antennas. However, omnidirectional antennas have low gain and diffuse coverage, weak wall penetration, and are susceptible to interference from the same or adjacent channels, resulting in poor link stability. Fixed-angle directional antennas have an unadjustable direction, making them unsuitable for situations where the router's location is unknown or the environment changes, leading to poor practical performance. Furthermore, some existing solutions employ router-side beamforming technology, but this technology relies on high-end routers and requires terminal collaboration, making it incompatible with existing home routers and unable to actively optimize the link from the camera side. In summary, existing solutions cannot achieve autonomous, dynamic, and adaptive antenna direction adjustment at the camera side, making it difficult to guarantee the connection reliability of fixed-installation terminals in complex environments. Summary of the Invention

[0003] To address the problem that existing technologies cannot achieve autonomous, dynamic, and adaptive antenna orientation control at the camera side to ensure connection reliability in complex dynamic environments, this application proposes a self-sensing beamforming antenna system and method for outdoor cameras. This system constructs a self-contained and self-sensing beamforming architecture on the terminal side, achieving autonomous link optimization and dynamic beam control independent of network-side devices.

[0004] To solve the above-mentioned technical problems, this application provides the following technical solution: This application proposes a self-sensing beamforming antenna system for an outdoor camera, comprising: a reconfigurable antenna array module including at least two antenna radiating elements, each antenna radiating element having its feed point connected to an independent adjustable matching network for independent phase / amplitude control; a radio frequency tuning and control module including the adjustable matching network and a driving circuit, the adjustable matching network including at least a signal-controlled phase shifter; the driving circuit being connected to the camera's master control decision unit, which receives digital control signals emitted by the camera and converts them into precise analog control voltages applied to the phase shifter; a channel sensing and processing module integrated into the camera, used to periodically acquire and analyze channel state information from a wireless router; and a master control decision unit, used to execute the entire process logic of scanning, calculation, locking, and tracking; and automatically triggering re-optimization when the link deteriorates to a threshold.

[0005] The above solution, by setting up a reconfigurable antenna array and RF tuning control module on the camera side and combining channel awareness and master control decision to form a closed loop, enables the terminal to autonomously calculate and apply optimal phase / amplitude modulation based on real-time channel status. This achieves self-aware beamforming independent of the router, fundamentally solving the problem of link degradation caused by the inability of fixed-installation terminals to dynamically and adaptively adjust antenna direction in complex environments.

[0006] More preferably, the antenna radiating element is a microstrip patch antenna printed on a flexible circuit board.

[0007] The above solution adopts a microstrip patch antenna on a flexible circuit board. By utilizing the flexibility and conformal characteristics of the FPC, the antenna radiating element can be closely fitted to the curved surface inside the device housing, which saves internal motherboard space and ensures the isolation and radiation performance of the antenna radiating element.

[0008] More preferably, the flexible circuit board is attached to the non-metallic area inside the camera housing.

[0009] The above solution avoids the shielding and attenuation of electromagnetic waves by attaching the FPC to the non-metallic area inside the outer casing, while making full use of the unused non-metallic space in the product ID design, achieving perfect compatibility between the antenna layout and the appearance and internal stacking of the device.

[0010] More preferably, the channel sensing and processing module has a built-in or associated processing unit for calculating the optimal phase parameters to be applied to each of the antenna radiating elements based on channel state information (CSI) data, and generating corresponding control commands to be sent to the phase shifter in the radio frequency tuning and control module.

[0011] The above scheme achieves a precise closed-loop conversion between channel-aware data and radio frequency tuning execution by using a built-in or associated processing unit to perform mapping calculations from CSI data to optimal phase parameters. This ensures the real-time performance and accuracy of beamforming pattern calculation, thereby effectively aligning the main lobe of the beam with the direction of the strongest signal and forming nulls in the direction of interference.

[0012] More preferably, the channel sensing and processing module is integrated into the camera's Wi-Fi main control chip.

[0013] The above solution integrates the channel sensing and processing module into the Wi-Fi main control chip, directly obtaining the most original and accurate channel state information at the source of the data link, reducing cross-chip communication latency, and at the same time utilizing the computing power of the existing SoC to complete the sensing processing, thereby reducing the system hardware cost and complexity.

[0014] Furthermore, this application also provides a self-sensing beamforming method for outdoor cameras, the method comprising: a training and scanning phase: controlling the radio frequency tuning and control module to switch the reconfigurable antenna array to multiple operating states in a predetermined tuning parameter space according to a preset sequence; a calculation and decision phase: based on the recorded CSI dataset, performing calculations through a preset optimization algorithm to evaluate the signal link quality in each state, and deciding on the optimal tuning parameter combination that aligns the main lobe of the reconfigurable antenna array beam with the direction of arrival of the strongest signal while suppressing interference as much as possible; an application and stable operation phase: applying the optimal tuning parameter combination to the radio frequency tuning and control module to lock the reconfigurable antenna array in the optimal state, establishing or optimizing the data communication link with the wireless router; and a tracking and re-optimization phase: continuously monitoring the performance indicators of the communication link during stable operation; triggering a new round of training and optimization when the monitored indicators drop below a preset threshold.

[0015] The above solution uses a closed-loop process of "scanning-computation-application-tracking" to enable the camera to autonomously traverse the tuning space to find the optimal beam state without the need for external sensors and routers to cooperate. It also automatically re-optimizes when environmental changes cause link degradation, thus achieving low-complexity and high-reliability terminal-side adaptive beamforming control.

[0016] More preferably, the training scanning phase described above further includes: acquiring and recording the corresponding channel state information data through the channel sensing and processing module in each state.

[0017] The above scheme establishes a complete and accurate channel response dataset for subsequent calculation and decision-making by synchronously acquiring and recording CSI data in each tuning state. This ensures that the data basis for optimal parameter decision-making covers the channel characteristics in all spatial directions and improves the accuracy of beam alignment.

[0018] More preferably, the tracking and re-optimization phase further includes: when the index is detected to have dropped beyond a preset threshold, returning to the training scanning phase to trigger a new round of training and optimization.

[0019] The above solution ensures that the system can promptly and automatically re-search for the optimal beam direction when encountering dynamic environmental interference such as personnel movement, furniture obstruction, or router location changes, by setting a clear degradation threshold and triggering a return to the training scan phase, thus guaranteeing the stability of the link during long-term operation.

[0020] In addition, this application also provides a self-sensing beamforming device for an outdoor camera, wherein the device includes a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to execute the method described above.

[0021] The above solution uses hardware cooperation between memory and processor to solidify the closed-loop control logic of self-sensing beamforming into executable instructions, enabling standard embedded computing platforms to run this adaptive method stably and reliably, thus improving the engineering feasibility and deployment consistency of the solution.

[0022] In addition, this application also provides a computer-readable medium having computer program instructions stored thereon, which can be executed by a processor to implement the method described above.

[0023] The above solution provides a software distribution carrier for the self-sensing beamforming control logic through a computer-readable medium, which enables the optimization method to be flexibly deployed in existing or newly produced outdoor camera equipment in the form of software upgrades or firmware burning, greatly reducing the cost of technology promotion and equipment upgrades.

[0024] Compared with the prior art, this application has the following technical effects: (1) Complete autonomy and backward compatibility: This application integrates all intelligent sensing and tuning functions into the channel sensing and processing module and main control decision unit on the camera side, without the need to upgrade or set any existing wireless routers in the user's home, achieving perfect backward compatibility and solving the pain point that the existing market cannot actively optimize the link from the terminal side.

[0025] (2) Significant performance improvement: This application adopts precise beamforming based on CSI data. Through the collaboration of the reconfigurable antenna array module and the radio frequency tuning and control module, it can not only concentrate the radiated energy to the optimal signal path and improve the equivalent link budget by 3-5dB, but also form nulls upwards in the interference by adjusting the beam pattern, thereby enhancing the main signal while actively suppressing interference, comprehensively improving the effective wireless throughput by 50%, significantly improving the stability of wireless transmission, reducing the probability of stuttering and disconnection, and improving the user experience.

[0026] (3) Strong engineering practicality and feasibility: In terms of structural design, this application adopts the design of FPC antenna unit attached to the non-metallic area inside the shell, which makes full use of the idle space of the product ID, does not occupy the core PCB motherboard area, and does not affect the original internal stacking and appearance; In terms of algorithm complexity, the “scan-calculate-apply-track” method proposed in this application has a small computational load and can run in real time on the remaining computing power of existing Wi-Fi SoC or main MCU without the need for an additional dedicated processor, and has high engineering feasibility and productization prospects. Attached Figure Description

[0027] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 A schematic diagram of the overall system architecture framework of an embodiment of this application. Figure 1 ; Figure 2 A schematic diagram of the overall system architecture framework of an embodiment of this application. Figure 2 ; Figure 3 : A schematic diagram of an outdoor camera structure according to an embodiment of this application; Figure 4 A schematic diagram of a single antenna element and its adjustable matching network according to an embodiment of this application. Figure 5 A flowchart of the self-sensing beamforming antenna system according to an embodiment of this application. Detailed Implementation

[0028] 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, and 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.

[0029] Example 1 Such as 1 and Figure 2As shown, this embodiment provides a self-sensing beamforming antenna system for outdoor cameras. The system constructs a self-contained closed-loop control architecture on the terminal side. Its overall hardware framework mainly includes four core modules: a reconfigurable antenna array module, a radio frequency tuning and control module, a channel sensing and processing module, and a main control decision unit. It should be understood that although the modules are shown with specific logical divisions and connection topologies, in other embodiments, these modules can be merged or further split according to the actual chip integration level, as long as the functional requirements of the terminal-side autonomous sensing and tuning closed loop are met. The system described in this embodiment is illustrative only and not restrictive.

[0030] The reconfigurable antenna array module includes at least two antenna radiating elements, each with its feed point connected to an independent adjustable matching network, enabling independent phase / amplitude control. Specifically, the reconfigurable antenna array module is the physical carrier for beamforming in the entire system. The spatial arrangement of at least two antenna radiating elements forms the foundation of the array, while the independent adjustable matching network is key to achieving dynamic beam reconfiguration. The "independent adjustable matching network" referred to in this application refers to a tuning circuit dedicated to each antenna radiating element, unaffected by the states of other elements, capable of independently changing the impedance characteristics of its feed point. When the independent adjustable matching network adjusts the feed phase, the electromagnetic waves radiated by each antenna radiating element superimpose in space, generating a phase difference, thus deflecting the main lobe of the synthesized beam. When adjusting the amplitude, it changes the weighting ratio of the radiated energy of each element, thereby shaping the beam shape and null depth. This independent phase and amplitude control mechanism allows the array to flexibly synthesize customized radiation patterns that concentrate energy on the strongest signal path while simultaneously suppressing nulls in the direction of interference, based on complex spatial channel environments. For example, adjustable matching networks can achieve impedance and phase shifts by changing the values ​​of series or parallel variable reactance elements. It should be understood that while this embodiment emphasizes independent control of phase and amplitude, in some simplified embodiments where cost is extremely critical, retaining only the phase control dimension can still achieve significant beam deflection and link improvement.

[0031] The radio frequency tuning and control module includes the adjustable matching network and a driving circuit. The adjustable matching network includes at least a signal-controlled phase shifter. The driving circuit is connected to the main control decision unit of the camera and receives the digital control signals emitted by the camera, converting them into precise analog control voltages applied to the phase shifter. Specifically, the radio frequency tuning and control module acts as a bridge between digital decision-making and radio frequency physical execution. The phase shifter is the core device in the adjustable matching network that directly changes the signal phase. It can be implemented in various forms, such as a digital phase shifter, a continuous phase shifter based on a variable capacitor array, or an adjustable impedance network, as long as it can change phase under signal control. The driving circuit receives digital control signals (e.g., control words transmitted via I2C, SPI, or PWM interfaces) from the main control decision unit and decodes and converts them into precise analog control voltages required by the phase shifter. This digital-to-analog conversion and voltage-driven process is crucial because the phase shift of the phase shifter usually has a specific nonlinear mapping relationship with the analog voltage at its control terminal. The drive circuit must provide a high-precision, low-noise analog voltage to ensure the angular resolution and pointing accuracy of beamforming and avoid the main lobe of the beam deviating from the optimal direction due to voltage drift.

[0032] The channel sensing and processing module, integrated into the camera, is used to periodically acquire and analyze channel state information from the wireless router. Specifically, this module is the source of the system's "self-sensing" capability. Its integration with the camera means that the terminal can autonomously acquire channel characteristics without relying on any special configuration or feedback protocols from network-side devices (such as routers). The channel state information (CSI) contains details of amplitude attenuation and phase shift of the wireless signal during multipath propagation, far more refined than the traditional RSSI (Received Signal Strength Indication). By periodically extracting and analyzing CSI, the camera can accurately perceive the spatial channel matrix between itself and the router, identify the strongest signal arrival path and the direction of most severe interference, providing high-resolution decision-making basis for subsequent beamforming.

[0033] The master control decision unit executes the entire process logic of scanning, calculation, locking, and tracking; when the link deteriorates to a threshold, it automatically triggers re-optimization. Specifically, the master control decision unit is the command center of the entire self-sensing closed-loop architecture. Its "scan-calculate-lock-track" logic constitutes a complete adaptive control loop. In the scanning phase, the master control decision unit controls the array to traverse a preset parameter space to collect channel responses in all directions; in the calculation phase, it determines the optimal phase / amplitude combination based on the collected data; in the locking phase, it applies the optimal parameters to the RF tuning and control module, ensuring the array operates stably in the best beam state; in the tracking phase, it continuously monitors the link health. The engineering significance of this closed-loop logic lies in its ability to give fixed outdoor cameras proactive survivability in complex dynamic environments. When the multipath environment changes abruptly due to personnel movement, furniture obstruction, or weather changes, and the link deteriorates to a preset threshold, the main control decision unit can automatically trigger re-optimization without manual intervention or instructions from the router side. It can quickly search for and lock a new optimal beam direction, thereby ensuring the long-term stability of the video transmission link.

[0034] Through the coordinated operation of the four modules mentioned above, the system in this embodiment establishes a complete closed-loop data flow at the camera side, from channel perception, data processing, decision generation to RF execution. The channel perception and processing module transmits the raw CSI data to the master control decision unit. The master control decision unit calculates the optimal tuning parameters and generates digital control signals, which are sent to the drive circuit of the RF tuning and control module. The drive circuit outputs an analog voltage to control the phase shifter in the reconfigurable antenna array module, ultimately changing the array pattern and affecting the channel reception quality again, forming a closed-loop feedback. This self-contained terminal-side architecture completely eliminates the dependence on the beamforming capabilities of existing routers, fundamentally solving the three major pain points of low gain of traditional omnidirectional antennas, the inability of fixed directional antennas to adapt to environmental changes, and the incompatibility of router-side beamforming with the existing market. This significantly improves the connection reliability of outdoor cameras in complex wall-penetrating and interference environments.

[0035] To further optimize the physical structure of the reconfigurable antenna array module to adapt to the compact internal space and complex electromagnetic environment of outdoor cameras, the morphology and layout of its antenna radiating element are described in the following section. Specifically, the antenna radiating element is a microstrip patch antenna printed on a flexible circuit board. More preferably, the flexible circuit board is attached to the non-metallic area inside the camera housing.

[0036] This embodiment establishes a creative defense mechanism of "casing-integrated FPC adjustable antenna array" by employing a microstrip patch antenna printed on a flexible circuit board. Traditional outdoor cameras typically use PCB motherboard antennas or LDS antennas. However, PCB motherboard antennas occupy valuable wiring area on the core motherboard and are highly susceptible to crosstalk and common-mode interference from high-speed digital signals on the motherboard (such as DDR memory clocks and image processor data buses). While LDS antennas can utilize the casing, their manufacturing costs are high and subsequent tuning is difficult. In contrast, the FPC microstrip patch antenna described in this application utilizes the flexibility and conformal characteristics of the flexible circuit board itself, allowing it to fit tightly onto curved or irregular surfaces inside the camera casing, such as... Figure 3 As shown, this design saves internal motherboard space while ensuring isolation and radiation performance between antenna radiating elements. This conformal design allows the antenna array to extend along the edge of the housing, thereby achieving a horizontal radiation angle of nearly 360 degrees, greatly expanding the adjustable range of beamforming in the spatial dimension.

[0037] Furthermore, attaching the flexible circuit board to the non-metallic area inside the camera housing is a necessary choice based on the principles of electromagnetic wave transmission and anti-interference engineering considerations. From the perspective of the necessity of electromagnetic transmission, if the antenna is attached to a metallic area or blocked by metal, electromagnetic waves will experience severe reflection and attenuation when penetrating the metal casing, leading to a sharp decrease in radiation efficiency and even the formation of electromagnetic shielding blind spots. Therefore, placing the FPC antenna in the unused non-metallic area reserved during product ID design (such as non-metallic inserts around the plastic cover or light-transmitting cover) ensures that electromagnetic waves are radiated and received with extremely low penetration loss. From an engineering perspective of keeping it away from interference sources, the motherboard area inside the camera is a strong concentration of electromagnetic interference sources. The image processor (ISP), motor drive circuits, etc., generate broadband radio frequency noise during operation. Attaching the FPC antenna to the inside of the housing, away from the motherboard, physically increases the distance between the antenna and the interference source, fundamentally reducing the gain of the noise coupling path, improving the signal-to-noise ratio of the CSI data acquired by the channel sensing and processing module, and providing a clean physical basis for subsequent precise beamforming calculations.

[0038] It should be understood that although this embodiment uses two antenna radiating elements as an example, the number of antenna elements in the reconfigurable antenna array module is not limited to this. As an equivalent alternative, the number of antenna elements can be 2, 3, or 4. When using a 2-element array, the system structure is the most streamlined and cost-effective, achieving basic beam deflection and interference immunity improvements. When using a 3-element array, the degrees of freedom in beamforming increase, enabling the formation of narrower main lobes and deeper nulls, significantly enhancing interference suppression. When using a 4-element array, the pattern control accuracy is optimal, achieving extremely high-gain directional transmission in complex indoor multipath environments, but the hardware complexity of the RF tuning and control modules and the computational load of the main control decision unit also increase accordingly. In actual product design, the configuration of 2, 3, or 4-element arrays can be flexibly selected based on target cost, available internal space, and expected link improvement indicators. The above description of antenna morphology and layout is illustrative only and not restrictive. Any physical implementation of an antenna that can achieve conformal integration and anti-interference isolation on the terminal side should be covered within the scope of protection of this application.

[0039] To further refine the specific execution logic and hardware carrier of channel sensing and data processing, the internal architecture and integration method of the channel sensing and processing module are described in an advanced design below. Specifically, the channel sensing and processing module has a built-in or associated processing unit for calculating the optimal phase parameters to be applied to each of the antenna radiating elements based on CSI data, and generating corresponding control commands to be sent to the phase shifter in the RF tuning and control module. More preferably, the channel sensing and processing module is integrated into the camera's Wi-Fi main control chip.

[0040] This embodiment achieves a binary binding of functional constraints and physical structure by assigning explicit underlying hardware and algorithm logic to the channel sensing and processing module. The core task of the processing unit is to map abstract CSI data into specific phase shifter control commands. The micro-mechanism of this mapping logic lies in the fact that CSI data contains details of amplitude attenuation and phase shift of wireless signals during spatial multipath propagation, essentially reflecting the characteristics of the current spatial channel matrix. The processing unit extracts channel gain indicators (such as signal-to-noise ratio or equivalent channel capacity) from the CSI data and performs calculation and evaluation using a preset low-complexity optimization algorithm. Specifically, this low-complexity optimization algorithm adopts a direct traversal comparison strategy, that is, in the CSI dataset corresponding to each tuning state recorded during the training scanning phase, it directly calculates and compares the estimated channel gain values ​​under each antenna phase combination, and then selects the phase combination corresponding to the highest gain value as the optimal phase parameter. This algorithm, which directly selects the phase combination corresponding to the highest channel gain, is simple in principle but highly practical for resource-constrained embedded IoT devices. It avoids complex matrix singular value decomposition or convex optimization iterative calculations, enabling decision-making within milliseconds and ensuring real-time beamforming response. It should be understood that while this embodiment describes a direct selection algorithm based on the highest channel gain, in other embodiments with more abundant computing power, this algorithm can be replaced by an algorithm based on minimum mean square error or a comprehensive evaluation algorithm based on zero-depression depth weighting, as long as an effective mapping from CSI data to optimal phase parameters can be achieved. The above description is illustrative only and not restrictive.

[0041] Furthermore, integrating the channel sensing and processing module into the camera's Wi-Fi main control chip is based on a dual consideration of data acquisition latency and system architecture simplification. From the perspective of low-latency advantage in acquiring raw CSI at the data link source, the Wi-Fi main control chip is the first-level processing entry point for the camera to receive wireless signals. The raw CSI data decoded at the physical layer is purest and acquired most instantly here. If the channel sensing and processing module is externalized to a separate chip, the raw CSI data needs to be transmitted to an external processor via an inter-chip interface (such as USB, SDIO, or SPI). This not only introduces additional communication latency but may also result in the loss of phase details or the introduction of timing asynchrony errors during high-speed data transfer, causing the calculated optimal phase parameters to become out of sync with the actual channel state. By embedding the sensing and processing module into the Wi-Fi main control chip, the system achieves an extremely short closed-loop path of on-site data retrieval, on-site calculation, and on-site generation of control commands at the data source, significantly shortening the response time from environmental changes to beam adjustment. From the perspective of system architecture simplification, this integration method directly utilizes the idle microprocessor computing power inside the existing Wi-Fi SoC, without the need to add an additional dedicated processor chip, which saves motherboard area and reduces material costs and power consumption.

[0042] However, it should be understood that the physical integration form of the channel sensing and processing module in this application is not limited to the aforementioned built-in method. As an equivalent alternative, if the Wi-Fi chip used in the camera is a pure radio frequency transceiver without baseband processing and computing power redundancy, the channel sensing and processing module can also be associated with an independent microcontroller unit (MCU) or digital signal processor (DSP) to undertake the computing task. In this alternative, the Wi-Fi chip is only responsible for extracting and outputting the raw CSI data. The external independent MCU or DSP receives the dataset through a serial bus and performs calculations using a low-complexity optimization algorithm, and then sends the generated control commands back to the main control decision unit to drive the phase shifter. Although this deployment of an independent processing unit slightly increases the response latency, it provides greater flexibility for system design, enabling the self-sensing beamforming architecture of this application to be compatible with more types and models of underlying Wi-Fi hardware, enhancing the solution's anti-circumvention capabilities and versatility. The above description of the processing unit algorithm logic and hardware integration is intended to establish a complete mapping from functional steps to physical execution carriers. Any combination of hardware and algorithms that can realize autonomous CSI calculation and phase instruction generation on the terminal side should be covered within the scope of protection of this application.

[0043] Example 2 like Figure 4 and Figure 5 As shown, this embodiment provides a self-sensing beamforming method for outdoor cameras. This method establishes a closed-loop control logic thread from the perspectives of timing and action, mirroring the system architecture described in Embodiment 1 in terms of timing and structure. Specifically, Embodiment 1 describes the physical module carriers supporting self-sensing beamforming and their connection relationships, while this embodiment details how these modules coordinate their actions along the time axis to achieve dynamic adaptive link optimization. The method of this embodiment mainly includes the following steps: Step S100, Training Scanning Phase: Control the radio frequency tuning and control module to enable the reconfigurable antenna array to switch between multiple working states according to a preset sequence within a predetermined tuning parameter space.

[0044] Specifically, this step is the starting point for exploring the entire closed-loop method. The so-called "predetermined tuning parameter space" refers to the set of parameter combinations formed by the adjustable ranges of the phase shifters in the independently adjustable matching network connected to each antenna radiating element. For example, in an array containing two antenna radiating elements, if each phase shifter supports phase adjustment from 0 degrees to 360 degrees, with a step resolution of 45 degrees, then the combination of the phase differences between the two phase shifters constitutes a tuning parameter space containing multiple discrete states. The so-called "switching according to a preset sequence" means that the master control decision unit sequentially sends digital control signals to the RF tuning and control module according to a specific traversal strategy (such as step-scanning phase differences). The drive circuit converts these signals into analog control voltages and applies them to the phase shifters, causing the array's radiation pattern to deflect sequentially in space, sweeping across different signal arrival directions. This step-scanning mechanism ensures the system's exhaustive exploration of spatial channel characteristics, avoiding the omission of optimal beam directions that might be caused by random jumps. It should be understood that although this embodiment uses step scanning as an example, in other embodiments where computing power or time is limited, random sampling scanning or local key scanning strategies based on historical prior knowledge can also be used, as long as the potential optimal parameter area can be covered. The above description is only illustrative and not restrictive.

[0045] Step S200, Calculation and Decision Stage: Based on the recorded CSI dataset, the signal link quality under each state is evaluated by a preset optimization algorithm, and the optimal combination of tuning parameters is determined so that the main lobe of the reconfigurable antenna array beam is aligned with the direction of arrival of the strongest signal while suppressing interference as much as possible.

[0046] Specifically, this step is the intelligent hub of the closed-loop method. During the training and scanning phase, the channel sensing and processing module synchronously acquires CSI data for each operating state. This data essentially reflects the spatial channel matrix response of the array under different radiation patterns. A pre-defined optimization algorithm evaluates these CSI datasets. Its micro-mechanism lies in the fact that adjusting the phase difference of each antenna radiating element can change the spatial energy distribution of the array's synthesized radiation pattern. When the optimal combination of tuning parameters is determined, its physical meaning is to achieve dual optimization of beamforming and null design. On one hand, this parameter combination causes the electromagnetic waves radiated by each element to superimpose in phase in the direction of the strongest signal arrival, forming a high-gain main lobe that concentrates the radiated energy to penetrate the optimal path. On the other hand, this parameter combination causes the electromagnetic waves to cancel out in phase upwards in the direction of strong interference, forming a low-gain null and actively suppressing co-channel or adjacent-channel interference sources. This synergistic design of main lobe alignment and null suppression not only improves the equivalent link budget by 3-5 dB but also fundamentally improves the effective wireless throughput. It should be understood that although this embodiment emphasizes the dual optimization of the main lobe and the null, in some simple scenarios where there is only a single strong path and no obvious directional interference, the algorithm can also be simplified to a single objective optimization that maximizes the main lobe gain. This still falls within the scope of the preset optimization algorithm of this application.

[0047] Step S300, Application and Stable Operation Phase: The optimal tuning parameter combination is applied to the RF tuning and control module to lock the reconfigurable antenna array in the optimal state, and to establish or optimize the data communication link with the wireless router.

[0048] Specifically, this step is the implementation of the closed-loop method. The main control decision unit encodes the optimal phase parameters determined in step S200 into digital control signals and sends them to the drive circuit of the RF tuning and control module. The drive circuit outputs a precise analog control voltage to lock the phase shifter's phase offset. At this point, the reconfigurable antenna array no longer switches states but remains stably in the optimal radiation pattern state with the main lobe aligned to the best path and null suppression of interference. In this stable state, the camera transmits high-throughput, low-latency video data with the wireless router, completely eliminating the stuttering and disconnection phenomena caused by low gain and interference in traditional omnidirectional antennas in wall-penetrating scenarios.

[0049] Step S400, Tracking and Re-optimization Phase: During stable operation, continuously monitor the performance indicators of the communication link; when the monitored indicators drop below a preset threshold, trigger a new round of training and optimization.

[0050] Specifically, this step is a mechanism to ensure the long-term stable operation of the closed-loop method. The wireless environment in which outdoor cameras operate is dynamic. For example, movement of people can change multipath reflection paths, or heavy rain can cause a sudden increase in signal path loss. These changes can gradually cause the originally locked optimal beam direction to become mismatched. Therefore, the main control decision unit must continuously monitor the core performance indicators of the link (such as Received Signal Strength Indicator (RSSI), packet error rate, or throughput) during stable operation. When the monitored indicators drop below a preset threshold, it indicates that the current beam pattern can no longer adapt to the new channel environment. The system automatically triggers re-optimization and returns to step S100 to start a new round of training scanning and decision calculation. This automatically triggered re-optimization mechanism gives the camera the ability to actively survive in complex and dynamic environments, quickly relocking the optimal beam without manual intervention, thus ensuring the long-term stability of the video transmission link. It should be understood that the specific setting of the preset threshold can be adjusted according to the fault tolerance requirements of different application scenarios. For example, for scenarios with extremely high smoothness requirements, a stricter threshold can be set (such as triggering when RSSI drops by more than 3dB), while for scenarios with higher latency tolerance, a more lenient threshold can be set. The above description is only illustrative and not restrictive.

[0051] Through the time sequence of steps S100 to S400 described above, the method of this embodiment constructs a complete control closed loop on the camera side, encompassing spatial exploration, intelligent decision-making, stable execution, and dynamic tracking. This method and the system architecture of Embodiment 1 are complementary; the system architecture provides the physical execution carrier for the method, while the method endows the system architecture with a dynamic operational spirit, jointly realizing the self-contained and self-aware beamforming capability on the terminal side.

[0052] The following section provides an advanced refinement of the key data acquisition nodes and re-optimization triggering logic in the self-sensing beamforming method, providing precise logical judgment criteria for the real-time operation of the algorithm and preventing functional steps from being abstracted.

[0053] First, the training and scanning phase described above also includes: acquiring and recording the corresponding channel state information data through the channel sensing and processing module in each state. Specifically, this embodiment emphasizes the strict synchronization between CSI data acquisition and antenna state switching. When the reconfigurable antenna array switches to the Nth working state according to a preset sequence within a predetermined tuning parameter space, the main control decision unit must ensure that within the short time window during which the state is stably maintained, the channel sensing and processing module completes the extraction and snapshot recording of CSI data from the wireless router, and establishes a mapping relationship between the CSI data and the current Nth phase parameter combination, storing it in the dataset. The micro-mechanism of this synchronous acquisition and recording is that CSI data is essentially the projection response of the spatial channel matrix under the current array pattern filtering. Only by ensuring a strict correspondence between the state and the data can the constructed CSI dataset completely and losslessly reflect the full picture of channel characteristics within the entire tuning parameter space. The completeness of the dataset is a prerequisite for the subsequent calculation and decision-making stages to accurately evaluate the link quality of each state and select the globally optimal tuning parameter combination. If there are timing misalignments or omissions in data acquisition, the decision algorithm will be evaluated based on distorted or incomplete channel responses, which can easily lead to local optima or cause the main lobe of the beam to deviate from the direction of arrival of the strongest signal, thereby weakening the gain effect of beamforming.

[0054] Secondly, the tracking and re-optimization phase also includes: when the detected index drop exceeds a preset threshold, returning to the training scan phase to trigger a new round of training and optimization. Specifically, this embodiment provides a clear micro-judgment standard and physical logic explanation for the functional limitation of "index drop exceeding the preset threshold". During stable operation, the main control decision unit continuously monitors the performance indicators of the communication link, which mainly include Received Signal Strength Indicator (RSSI) and packet error rate. The specific judgment standard for the preset threshold can be set as follows: when the detected RSSI drop exceeds 5dB, or when the detected packet error rate shows an upward trend for several consecutive statistical periods (e.g., three consecutive 10-second periods) and exceeds 1%, it is determined that the link degradation exceeds the threshold. A 5dB drop in RSSI means that the current equivalent link budget has been lost by nearly two-thirds, and the video transmission bitrate will deteriorate sharply; while the continuous rise in packet error rate directly reflects the retransmission storm caused by multipath interference, which is a precursor to stuttering and disconnection. When any of the above judgment criteria are met, the system automatically returns to the training scan phase and triggers a new round of optimization timing logic. This triggering mechanism gives the camera the ability to survive actively in dynamic environments, and it can respond quickly to environmental changes without human intervention.

[0055] It should be understood that when triggering a new round of training and optimization, the scanning strategy is not static, but can flexibly select between local fast scanning and full scanning strategies based on the degree and type of degradation. When the detected index decreases slightly (e.g., RSSI decreases between 5dB and 8dB), or when index fluctuations exhibit brief transient characteristics, the system can prioritize the local fast scanning strategy. In this case, the master control decision unit uses the currently locked optimal parameter as the center and only performs step-by-step traversal among a few phase difference states in its vicinity to quickly find suboptimal compensation parameters. This strategy is extremely time-consuming, usually completed within tens of milliseconds, and can minimize the impact of interruptions on ongoing video data transmission. However, when the detected index deteriorates drastically (e.g., RSSI decreases by more than 10dB), or when the spatial multipath environment is fundamentally reconstructed due to router relocation or the movement of large furniture, and there are no suitable compensation solutions near the original globally optimal parameters, the system automatically switches to the full scanning strategy, retracing the entire predetermined tuning parameter space to find a new globally optimal beam direction. By intelligently switching between local rapid scanning and full scanning, the system achieves a dynamic balance between response speed and search accuracy, ensuring both rapid self-healing from minor fluctuations and link reconstruction capabilities under drastic environmental changes. The above descriptions regarding data acquisition synchronization, degradation judgment criteria, and scanning strategy selection are illustrative and not restrictive. Any logical design capable of achieving precise data mapping and dynamic threshold triggering should be covered within the scope of this application.

[0056] To more clearly illustrate the irreplaceable nature of the self-contained closed-loop architecture and reconfigurable antenna array on the terminal side of this application, several typical counterexamples are explained in detail below. It should be understood that these counterexamples are merely illustrative, not restrictive, and are intended to establish a defensive depth for the key features of this application by analyzing the microscopic mechanistic defects of existing technologies.

[0057] First, if a traditional omnidirectional antenna is used, it will face low gain and inability to suppress interference in typical wall-penetrating scenarios, leading to stuttering and disconnections. Specifically, the radiation pattern of an omnidirectional antenna is uniformly distributed in the horizontal plane, and its physical mechanism dictates that energy is evenly distributed in all 360 degrees. When an outdoor camera and an indoor router need to establish a directional high-throughput link through a wall, the omnidirectional antenna cannot concentrate the radiated energy in the optimal path direction for wall penetration, resulting in a severe shortage of the equivalent link budget. More critically, in complex home wireless environments, co-channel or adjacent-channel interference sources (such as a neighbor's router, microwave oven, etc.) are distributed in different directions. Due to the lack of spatial selectivity, the omnidirectional antenna will indiscriminately receive interference signals from all directions, failing to form nulls in the direction of interference. This dual degradation of gain dispersion and complete interference reception directly results in an extremely low physical layer signal-to-noise ratio, thus triggering stuttering and disconnections even at slightly higher video bitrates.

[0058] Secondly, if a fixed directional antenna is used, beam mismatch will occur, leading to link interruptions when the router's location changes. While a fixed directional antenna can be manually adjusted during initial installation to align the main lobe of the beam with the router for higher gain, its directional characteristics... Figure 1 Once fixed, a fixed antenna loses its dynamic reconfiguration capability. In practical use, users often change the physical location of their routers due to home layout adjustments, router relocation, or replacement. At this time, the main lobe of the originally aligned beam may deviate from the direction of the new strongest signal, or even be aligned with a new source of strong interference. Because fixed antennas cannot autonomously sense channel changes and readjust phase / amplitude parameters at the terminal side, this beam mismatch leads to a sharp drop in link budget, the consequences of which are often more severe than with omnidirectional antennas, easily causing a complete link outage.

[0059] Finally, relying solely on router-side beamforming will fail to deliver a solution due to incompatibility with existing routers and the inability to proactively optimize from the camera side. Router-side beamforming (such as MIMO Beamforming based on the 802.11ac / ax standard) requires both the router and the terminal to support specific feedback protocols (such as SU / MU Beamforming), and the router needs multi-antenna arrays and high-performance baseband chips to calculate and generate the Steering Matrix. However, in the vast existing home market, the vast majority of users are still using low-end single-antenna / dual-antenna routers that only support 802.11n or earlier ac standards. These routers lack beamforming transmission capabilities and cannot parse the terminal's feedback frames. If the system architecture of this application relies on router-side beamforming coordination, it will be completely ineffective against these existing routers. Furthermore, even if the router supports beamforming, its optimization goal is usually global throughput rather than the specific wall-penetrating link quality at the camera side, and the camera, as the receiving end, cannot actively trigger the router to adjust the beam direction to adapt to dynamic changes in its environment. This passive architecture, which relies on network-side devices, fundamentally deprives the terminal of its right to proactively optimize the link.

[0060] The above comparison clearly shows that traditional omnidirectional antennas and fixed directional antennas cannot achieve dynamic energy concentration and spatial interference suppression at the physical layer mechanism, while router-side beamforming faces insurmountable gaps in engineering implementation and market compatibility. This application, by constructing a self-aware closed-loop architecture on the camera side, including a reconfigurable antenna array module, an RF tuning and control module, a channel sensing and processing module, and a main control decision unit, completely eliminates dependence on router-side capabilities, granting the terminal complete control over autonomous channel sensing and dynamic adjustment of beam main lobe and nulls. This terminal-side self-contained closed-loop design not only achieves dual optimization of directional gain and anti-interference nulls at the physical mechanism level, but also achieves perfect backward compatibility with existing routers in terms of engineering ecosystem. Its technological improvement is abrupt rather than nonlinear, possessing irreplaceable creative value.

[0061] Example 3 This embodiment provides a self-sensing beamforming device for outdoor cameras. From a hardware and software perspective, this device provides a concrete physical operating platform for the aforementioned method flow, solidifying the abstract closed-loop control logic into a combination of hardware entities and firmware code that can be directly observed for infringement evidence collection.

[0062] The device includes a memory for storing computer program instructions and a processor for executing the computer program instructions. When the computer program instructions are executed by the processor, the device is triggered to execute the method described above. Specifically, this embodiment establishes a deep integration between software logic and physical chips by clearly defining the specific hardware forms of the memory and processor. The processor is physically manifested as a system-on-a-chip (SOC) for the camera. This SOC integrates an ARM core or a RISC-V core to provide computing power, and also integrates the Wi-Fi baseband processing module and main control decision unit mentioned in Embodiment 3. When the computer program instructions are executed by the SOC, its internal computing logic is scheduled to sequentially issue digital control signals, extract CSI datasets, run low-complexity optimization algorithms, and monitor link performance indicators according to the timing steps described in Embodiment 2 or 3, thereby truly triggering and completing the entire process of self-sensing beamforming at the physical chip level. The memory is physically manifested as a non-volatile memory chip, such as NOR Flash memory or NAND Flash memory, which is connected to the SOC via SPI or a parallel bus. The computer program instructions are burned into the Flash memory before the device leaves the factory. Even after the device is powered off and restarted, these instructions are still intact, ensuring that the camera can be automatically loaded and has self-sensing beamforming capability every time it is powered on and initialized, without relying on an external server to send the algorithm in real time.

[0063] It should be understood that although this embodiment describes a typical architecture where the memory is a separate Flash chip and the processor is an integrated main control SOC, in other resource-constrained or architecturally different embodiments, the physical form of the memory and processor can have various equivalent alternatives. For example, in some highly integrated miniature camera modules, the memory can also be an eMMC storage module or ROM area embedded inside the main control SOC, thereby further saving motherboard wiring area; in addition to the main control SOC, the processor can also be associated with an independent microcontroller unit (MCU) or digital signal processor (DSP) as a coprocessor, specifically used to execute beamforming calculation and decision instructions to share the real-time load of the main control SOC. As long as the hardware combination can provide a physical environment for storing and executing the computer program instructions, and can trigger the device to complete the closed-loop action of training scanning, calculation decision, application locking, and tracking re-optimization during instruction execution, it should be covered within the protection scope of this application.

[0064] Through the hardware collaboration between the memory and processor described above, the device in this embodiment transforms the closed-loop control logic of self-sensing beamforming from a purely theoretical scheme into an engineering entity that can be mass-produced and deployed. This hardware-software bundled design not only enhances the visibility of infringement evidence collection, allowing for direct proof of infringement in forensic examinations by reading and disassembling the code logic in Flash memory and the pin control signals of the SOC, but also ensures the stability and consistency of the algorithm running on resource-constrained IoT terminals, fundamentally supporting the improvement of connection reliability of outdoor cameras in complex and dynamic environments. The above description is illustrative only and not restrictive.

[0065] Example 4 This embodiment provides a computer-readable medium storing computer program instructions that can be executed by a processor to implement the method described. Specifically, this embodiment provides independent carrier protection for the aforementioned self-sensing beamforming method from the perspective of software distribution and firmware upgrades, enabling abstract control logic to be widely disseminated and deployed in the form of data, independent of specific hardware entities.

[0066] The term "computer-readable medium" as used in this application refers to any physical or logical storage medium that can be read by a processor of a computing device and from which instructions can be extracted for execution. In the specific engineering context of an outdoor camera, the computer-readable medium can take various physical forms. For example, it could be a TF card inserted into the camera's card slot, a portable medium that allows technicians or users to directly copy firmware files containing self-sensing beamforming logic to the device for local upgrades while the device is offline; alternatively, it could be a Flash memory chip on the camera's motherboard, such as the aforementioned NOR Flash or NAND Flash, where computer program instructions are burned into the Flash memory chip before the device leaves the factory, residing permanently as a low-level component of the device's firmware; or it could be a cloud download medium, i.e., a remote storage space provided by an internet server, from which the camera, when connected to the internet, downloads and installs a firmware upgrade package containing the aforementioned method via an OTA mechanism.

[0067] It should be understood that although this embodiment lists three typical media forms, namely TF card, Flash storage chip and cloud download carrier, in other data distribution scenarios, computer-readable media can also be optical disc, USB flash drive or even temporary data buffer transmitted through short-range communication protocols, as long as it can stably carry the computer program instructions and be extracted and executed by the processor. The above description is only illustrative and not restrictive.

[0068] Through the deployment of the aforementioned computer-readable medium, this embodiment achieves a technically valuable engineering effect: enabling existing outdoor cameras to acquire self-sensing beamforming capabilities through firmware upgrades, fundamentally solving the pain points of the existing market. In the vast security monitoring market, existing cameras already deployed in countless homes generally use traditional omnidirectional or fixed directional antennas. These devices are prone to lag and disconnection when faced with wall penetration loss and environmental interference. However, since the hardware is already fixed, performance cannot be improved by replacing the physical antenna. However, as explained in Embodiments 1 and 2 above, the core of this application lies in the self-contained closed-loop control logic on the terminal side. As long as the camera's main control SOC has remaining computing power and the RF front-end has an adjustable matching network and phase shifter (which is standard hardware in many mid-to-high-end cameras), then the originally idle hardware resources can be awakened through firmware upgrades. When the computer program instructions containing the described method are read from and executed from the computer-readable medium, existing cameras that originally only had basic Wi-Fi connectivity instantly acquire advanced intelligence such as autonomous channel sensing, dynamic phase scanning, locking the optimal beam, and automatically re-optimizing when the link deteriorates. This mechanism, which empowers existing hardware with software logic, not only avoids the huge cost of replacing devices for users, but also achieves perfect backward compatibility with existing home routers in terms of ecosystem compatibility. This allows older devices to improve the equivalent link budget by 3 to 5 dB without any external collaboration, thus comprehensively improving the effective wireless throughput. The improvement in its technical effect is abrupt rather than linear, and it has irreplaceable creative value.

[0069] To more clearly illustrate the operational effectiveness and engineering reliability of the self-contained closed-loop architecture and reconfigurable antenna array on the terminal side in real-world industry scenarios, a detailed explanation is provided below using the dynamic adaptive application scenario of an outdoor PTZ camera in windy and rainy environments. It should be understood that this scenario is illustrative only, not restrictive, and aims to demonstrate the complete lifecycle from device installation and power-on to sudden environmental changes. Any wireless terminal application exhibiting similar dynamic changes in multipath interference and path loss should be covered within the scope of protection of this application.

[0070] A typical scenario is set as follows: an outdoor PTZ camera is installed under the eaves, while the wireless router is located indoors, separated from the camera by two load-bearing walls. In this scenario, the wireless signal must undergo severe penetration attenuation and complex indoor multipath reflections, making traditional omnidirectional antennas prone to video stuttering and disconnection. When the camera is first powered on and initialized, its internal main control decision unit immediately and autonomously initiates the self-sensing beamforming method process.

[0071] During the training and scanning phase, the main control decision unit controls the radio frequency tuning and control module, enabling the reconfigurable antenna array to switch between multiple operating states according to a preset sequence within a predetermined tuning parameter space. Specifically, as illustrated in the structural diagram, the antenna radiating element of the reconfigurable antenna array module is a microstrip patch antenna printed on a flexible circuit board, and the flexible circuit board is attached to the non-metallic area inside the camera housing. In the actual physical layout of the PTZ camera, two FPCs printed with microstrip patch antennas are respectively attached to the edges of the non-metallic light-transmitting covers on the left and right sides of the lower half of the PTZ camera's outer shell. This layout utilizes the conformal characteristics of the FPC, allowing the antenna to extend along the curved surface of the PTZ camera, achieving a horizontal radiation angle of nearly 360 degrees, while staying away from strong interference sources such as the image processor and motor drive located in the upper half of the PTZ camera's mainboard area. During the scanning process, the main control decision unit sequentially sends digital control signals, which are converted into analog control voltages by the drive circuit and applied to the phase shifters in the independently adjustable matching network connected to the feed point of each antenna radiating element. This causes the array beam to deflect in steps in the horizontal plane, scanning different wall-penetrating and reflection paths. In each state, the channel sensing and processing module synchronously acquires and records the corresponding channel state information data.

[0072] The calculation and decision-making phase then begins. The processing unit, either built into or associated with the Wi-Fi main control chip, calculates the optimal phase parameters to be applied to each antenna radiating element based on the recorded CSI dataset. This processing unit uses a low-complexity optimization algorithm to directly select the optimal combination of tuning parameters that aligns the main lobe of the beam with the direction of the strongest signal while suppressing interference as much as possible. For example, the optimal phase combination determined by the algorithm causes the electromagnetic waves radiated by the two antenna radiating elements to superimpose in phase on the direct path through the two walls, forming a high-gain main lobe, while canceling out of phase on the lateral reflection path of interference from the neighboring router, forming a null.

[0073] Upon entering the application and stable operation phase, the main control decision unit applies the optimal combination of tuning parameters to the RF tuning and control module, locking the reconfigurable antenna array into this optimal state and establishing a high-throughput data communication link with the wireless router. At this point, the camera's video stream can be transmitted smoothly, and the equivalent link budget is improved by approximately 4dB compared to a traditional omnidirectional antenna.

[0074] During stable operation, the system enters a tracking and re-optimization phase, continuously monitoring the performance indicators of the communication link. At this point, a sudden change occurs in the simulated scenario: a heavy rainstorm. Raindrops cause severe absorption and scattering of 2.4GHz electromagnetic waves, leading to a sudden increase in the loss of the strongest signal path that previously penetrated two walls. Simultaneously, the water film formed by rainwater on the eaves and window glass surfaces alters the multipath reflection coefficient, introducing new interference paths. This sudden environmental change causes the system to detect a drop in the Received Signal Strength Index (RSSI) exceeding a preset threshold of 5dB, and the packet error rate continues to rise.

[0075] When the detected index drop exceeds a preset threshold, the master control decision unit automatically returns to the training scan phase, triggering a new round of training and optimization. Since this degradation was mainly caused by fine-tuning of path characteristics due to raindrop scattering, and the spatial multipath environment did not undergo fundamental reconstruction, the system intelligently selected a local fast scanning strategy. The master control decision unit, centered on the currently locked optimal parameters, only performs step-by-step traversal between a few adjacent phase difference states. Within an extremely short period of tens of milliseconds, the channel sensing and processing module recaptures the CSI data characteristics under rain conditions, and the processing unit quickly determines a new optimal combination of tuning parameters. The new parameter combination allows for fine-tuning of the beam main lobe to avoid the subpath with the most severe raindrop scattering, while simultaneously re-forming null suppression against newly added rain reflection interference. After the array locks onto the new parameters, the RSSI quickly recovers, and video transmission returns to smooth operation.

[0076] The complete operation process in the aforementioned real-world scenarios clearly demonstrates that this application, by constructing a self-contained closed-loop architecture on the camera side and coordinating the conformal layout of the FPC antenna within the PTZ camera housing, endows the fixed-installation terminal with proactive survivability in complex dynamic environments. Whether it's the initial wall-penetrating path search during installation or rapid self-healing during sudden environmental changes such as heavy rain, the system can autonomously complete the dynamic reconstruction of beamforming and null suppression without manual intervention or router-side coordination, fundamentally solving the link stability pain point in the field of outdoor security monitoring. The above description is illustrative only and not restrictive.

[0077] The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. The preferred embodiments have been described in detail. Those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application, and all such modifications and substitutions should be covered within the scope of the claims of this application.

Claims

1. A self-sensing beamforming antenna system for outdoor cameras, characterized in that, include: A reconfigurable antenna array module includes at least two antenna radiating elements, each of which has a feed point connected to an independent adjustable matching network to achieve independent phase / amplitude control. The radio frequency tuning and control module includes the adjustable matching network and the driving circuit. The adjustable matching network includes at least a phase shifter controlled by a signal. The driving circuit is connected to the main control decision unit of the camera and is used to receive the digital control signal emitted by the camera and convert it into a precise analog control voltage applied to the phase shifter. The channel sensing and processing module, integrated into the camera, is used to periodically acquire and analyze channel state information from the wireless router. The master control decision unit is used to execute the entire process logic of scanning, calculation, locking, and tracking; when the link deteriorates to a threshold, it automatically triggers re-optimization.

2. The self-sensing beamforming antenna system for outdoor cameras according to claim 1, characterized in that, The antenna radiating element is a microstrip patch antenna printed on a flexible circuit board.

3. The self-sensing beamforming antenna system for outdoor cameras according to claim 2, characterized in that, The flexible circuit board is attached to the non-metallic area inside the camera housing.

4. The self-sensing beamforming antenna system for outdoor cameras according to claim 1, characterized in that, The channel sensing and processing module has a built-in or associated processing unit for calculating the optimal phase parameters to be applied to each of the antenna radiating elements based on CSI data, and generating corresponding control commands to be sent to the phase shifter in the radio frequency tuning and control module.

5. The self-sensing beamforming antenna system for an outdoor camera according to any one of claims 1 to 4, characterized in that, The channel sensing and processing module is integrated into the camera's Wi-Fi main control chip.

6. A self-sensing beamforming method for outdoor cameras, characterized in that, Applied to the system according to any one of claims 1-5, the method comprises: Training and scanning phase: Control the radio frequency tuning and control module to enable the reconfigurable antenna array to switch between multiple working states in a preset sequence within a predetermined tuning parameter space; Calculation and decision-making stage: Based on the recorded CSI dataset, calculations are performed using a preset optimization algorithm to evaluate the signal link quality under each state and to determine the optimal combination of tuning parameters that enables the main lobe of the reconfigurable antenna array beam to be aligned with the direction of arrival of the strongest signal while suppressing interference as much as possible. Application and stable operation phase: The optimal combination of tuning parameters is applied to the radio frequency tuning and control module to lock the reconfigurable antenna array in the optimal state and establish or optimize the data communication link with the wireless router; Tracking and Re-optimization Phase: During stable operation, continuously monitor the performance indicators of the communication link; when the monitored indicators drop below a preset threshold, trigger a new round of training and optimization.

7. The method according to claim 6, characterized in that, The training and scanning phase described above also includes: acquiring and recording the corresponding channel state information data through the channel sensing and processing module in each state.

8. The method according to claim 6 or 7, characterized in that, The tracking and re-optimization phase also includes: when the index is detected to have dropped beyond a preset threshold, returning to the training scanning phase to trigger a new round of training and optimization.

9. A self-sensing beamforming device for an outdoor camera, wherein, The device includes a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to perform the method of any one of claims 6 to 8.

10. A computer-readable medium having stored thereon computer program instructions that can be executed by a processor to implement the method as described in any one of claims 6 to 8.

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