An unmanned aerial vehicle-borne electromagnetic spectrum sensing method, device and readable storage medium

Abstract

The application provides a kind of unmanned aerial vehicle electromagnetic spectrum sensing method, equipment and readable storage medium, comprising: S1: receiving wide frequency band electromagnetic signal, according to unmanned aerial vehicle flight attitude and electromagnetic environment change automatically adjusts antenna direction and polarization mode;S2: the electromagnetic signal is filtered, amplified and frequency conversion preprocessing;S3: preset data acquisition and processing unit and integrate analog-to-digital converter and digital signal processor in it, the signal conditioning unit output preprocessed signal is digitized conversion and spectrum analysis, obtain signal frequency, amplitude and phase parameters;S4: with unmanned aerial vehicle flight control system establishes communication link, receives the flight state information of the unmanned aerial vehicle flight control system and feedback data acquisition and processing unit obtains the spectrum sensing result, while receiving remote instruction adjustment equipment parameters through ground control station.The application can be carried on unmanned aerial vehicle, can accurately perceive, analyze and process spectrum in complex electromagnetic environment.

Description

Technical Field

[0001] This invention relates to the fields of electromagnetic spectrum monitoring technology and UAV application technology, and in particular to a method, device and readable storage medium for UAV-borne electromagnetic spectrum sensing. Background Technology

[0002] In recent years, wireless communication technology has experienced explosive growth, with various radio services such as mobile communication, the Internet of Things, aviation navigation, emergency intercom, and military communication becoming increasingly widespread. This has led to a growing scarcity and congestion of electromagnetic spectrum resources, and a more complex electromagnetic environment in low-altitude, ground, and near-ground space. Simultaneously, in numerous fields such as national defense, public safety, emergency communications, aerospace, low-altitude airspace control, and radio surveillance, the demand for real-time monitoring, precise positioning, efficient management, and anomaly warning of the electromagnetic spectrum continues to rise. Spectrum management capabilities have become a core support for ensuring smooth communication, maintaining airspace security, and executing special missions.

[0003] Traditional electromagnetic spectrum sensing relies primarily on fixed ground monitoring stations and vehicle-mounted mobile monitoring equipment, which have significant limitations. Fixed monitoring stations have fixed locations and limited coverage, resulting in numerous blind spots and making it difficult to cover special areas such as mountainous regions, sea areas, remote suburbs, and high altitudes. While vehicle-mounted equipment offers mobility, it is constrained by terrain, road conditions, traffic control, and site conditions, preventing it from quickly reaching high-risk areas, restricted airspace, or operating over complex terrain. Both types of equipment struggle to achieve large-scale, three-dimensional, and dynamic spectrum sensing. In complex electromagnetic environments, they are prone to problems such as incomplete signal capture, inaccurate direction finding and positioning, insufficient real-time performance, and incomplete situational awareness, failing to meet the comprehensive, precise, and real-time requirements of modern spectrum management.

[0004] With its unique advantages such as mobility, rapid deployment, convenient takeoff and landing, wide operating range, low-altitude hovering capability, and rapid arrival at target airspace, the UAV platform perfectly compensates for the shortcomings of traditional ground-based spectrum monitoring equipment, making it the preferred carrier for carrying spectrum sensing equipment to achieve comprehensive three-dimensional spectrum monitoring. By carrying specialized equipment, UAVs can quickly establish mobile monitoring nodes in the air, enabling high-altitude overhead monitoring of target areas, blind spot coverage monitoring, and dynamic cruise monitoring. They can complete large-scale spectrum surveys as well as pinpoint investigation and precise location of suspicious signals and interference sources, adapting to diverse and complex mission scenarios.

[0005] However, currently available mainstream electromagnetic spectrum sensing devices significantly increase the load on drones during operation, shortening flight time and reducing flight stability. Some devices have excessively high power consumption, making them incompatible with the drone's power supply system and unable to operate continuously for extended periods. They also cannot adapt to the turbulence, vibrations, and complex electromagnetic interference environments encountered during drone flight, making them prone to data distortion, signal loss, and equipment malfunctions. Furthermore, the lack of signal acquisition and direction-finding algorithms optimized for drone flight attitude and high-speed movement characteristics leads to a significant decrease in monitoring accuracy, making it difficult to meet the requirements of practical combat missions.

[0006] Therefore, it is necessary to study an unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing method, device, and readable storage medium to address the shortcomings of existing technologies and solve or mitigate one or more of the aforementioned problems. Summary of the Invention

[0007] In view of this, the present invention provides an unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing method, device and readable storage medium, which can be mounted on a UAV and can accurately sense, analyze and process the spectrum in a complex electromagnetic environment.

[0008] On one hand, the present invention provides an unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing method, which includes the following steps: S1: Receives wideband electromagnetic signals through a preset spectrum sensing antenna array. The spectrum sensing antenna array uses a combination of multiple antennas to cover different frequency bands and has an adaptive adjustment function to automatically adjust the antenna direction and polarization according to the UAV's flight attitude and electromagnetic environment changes. S2: The electromagnetic signals received by the spectrum sensing antenna array are filtered, amplified, and frequency-converted preprocessed by a preset signal conditioning unit; S3: A preset data acquisition and processing unit is established, which integrates an analog-to-digital converter and a digital signal processor. The preprocessed signal output by the signal conditioning unit is digitally converted and subjected to spectrum analysis to obtain the signal frequency, amplitude and phase parameters. S4: The preset communication control unit establishes a communication link with the UAV flight control system, receives the flight status information of the UAV flight control system and feeds back the spectrum sensing results obtained by the data acquisition and processing unit to the UAV flight control system, and at the same time receives remote commands through the ground control station to adjust the equipment parameters.

[0009] In addition to the aspects and any possible implementations described above, an implementation is further provided, wherein S1 specifically includes: The spectrum sensing antenna array is configured as a multi-element antenna combination, which includes an omnidirectional antenna and a directional antenna, wherein the omnidirectional antenna is used for low-frequency signal reception and the directional antenna is used for high-frequency signal reception. The adaptive adjustment function acquires the pitch, roll, and yaw angles of the UAV through the built-in inertial measurement unit, which outputs attitude angle data. The adaptive adjustment function obtains the surrounding electromagnetic signal intensity distribution through the electromagnetic environment monitoring unit, and the electromagnetic environment monitoring unit outputs signal intensity distribution data. The antenna orientation and polarization are adjusted based on the fusion result of the attitude angle data and the signal strength distribution data.

[0010] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein S2 specifically includes: The interference signals in different frequency bands are filtered out by multi-stage filters to obtain the filtered signal; The filtered signal is amplified by a low-noise amplifier to obtain an amplified signal; The amplified signal is converted into an intermediate frequency signal by a frequency conversion circuit, and the intermediate frequency signal is used as the input of the data acquisition and processing unit.

[0011] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein S3 specifically includes: An analog-to-digital converter converts a preprocessed signal into a digital signal, which retains electromagnetic spectrum information. The digital signal processor performs a fast Fourier transform on the digital signal to obtain the signal's frequency, amplitude, and phase parameters; The digital signal processor identifies the signal modulation method based on the signal frequency, amplitude, and phase parameters, and the signal modulation method includes amplitude modulation, frequency modulation, and phase shift keying. The data acquisition and processing unit constructs an electromagnetic spectrum diagram based on the identified signal modulation method, and the electromagnetic spectrum diagram represents the spectrum sensing result.

[0012] In addition to the aspects and any possible implementations described above, an implementation is further provided, wherein S4 specifically includes: The system acquires flight status information, including the UAV's position, speed, and altitude, and transmits this flight status information using a wireless communication interface. The ground control station transmits remote commands via satellite communication, which include spectrum scanning range and resolution adjustment parameters. The adaptive adjustment parameters of the spectrum sensing antenna array are adjusted according to the remote command.

[0013] As described above and in any possible implementation, a further implementation is provided in which the adaptive adjustment in S1 includes: The inertial measurement unit outputs the attitude angle data to the control unit in real time, and the control unit fuses the attitude angle data. The electromagnetic environment monitoring unit outputs the signal strength distribution data to the control unit in real time, and the control unit integrates the signal strength distribution data. The control unit determines antenna optimization parameters based on the fused data, and the antenna optimization parameters include direction adjustment values ​​and polarization mode adjustment values. The spectrum sensing antenna array is adjusted according to the antenna optimization parameters, and the adjusted antenna receives optimized electromagnetic signals.

[0014] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the digital signal processor in S3 identifies the signal modulation method based on the signal frequency, amplitude, and phase parameters. The signal modulation method includes amplitude modulation, frequency modulation, and phase shift keying, specifically including: The Fast Fourier Transform is used to calculate the spectral components of the digital signal to obtain preliminary spectral data; Signal features are extracted based on the preliminary spectrum data, and the signal features include modulation type and bandwidth; The data acquisition and processing unit stores the electromagnetic spectrum and the signal characteristics.

[0015] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the process of the digital signal processor in S3 performing a fast Fourier transform on the digital signal to obtain the signal frequency, amplitude, and phase parameters specifically includes: Perform a spectrum scan, scanning the electromagnetic spectrum according to the preset frequency band range and scan step size to obtain scanned spectrum data; An electromagnetic signal feature database is established, and the scanned spectrum data is compared with the electromagnetic signal feature database to determine the signal classification result; The electromagnetic environment assessment index is calculated by combining the scanned spectrum data and the flight status information. The electromagnetic environment assessment index includes signal strength distribution and spectrum occupancy rate.

[0016] In accordance with the aspects and any possible implementations described above, an unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing device is further provided, the UAV-borne electromagnetic spectrum sensing device comprising: at least one processor; and a memory communicatively connected to the at least one processor; the memory storing instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the UAV-borne electromagnetic spectrum sensing method.

[0017] In addition to the aspects described above and any possible implementations, a readable storage medium is further provided, on which a computer program is stored, which, when executed, implements the UAV-borne electromagnetic spectrum sensing method.

[0018] Compared with the prior art, the present invention can achieve the following technical effects: (1) High mobility and wide-area monitoring: Relying on the UAV platform, it can quickly reach the target area, break through the geographical limitations of ground monitoring, and realize real-time monitoring of large-area complex electromagnetic environment. Whether in remote mountainous areas, ocean skies or urban areas with high-rise buildings, it can be flexibly deployed, greatly expanding the range and efficiency of electromagnetic spectrum sensing; (2) Precise spectrum sensing: The combination of multi-electrode antenna array and advanced signal processing technology has high sensitivity and high resolution spectrum sensing capabilities, which can accurately capture weak electromagnetic signals and accurately identify various signal characteristics, providing reliable data support for electromagnetic spectrum management and decision-making; (3) Intelligent adaptive adjustment: The equipment can automatically adjust its working parameters according to the flight status of the UAV and changes in the electromagnetic environment, always maintain the best monitoring performance, adapt to complex and ever-changing actual working conditions, reduce manual intervention, and improve the automation level of monitoring work; (4) Multifunctional integration: It integrates multiple functions such as spectrum scanning, signal recognition, environmental assessment, data storage and transmission, to meet the diverse needs of different fields and tasks for electromagnetic spectrum sensing, and to provide a one-stop solution for electromagnetic spectrum monitoring and management. (5) Collaborative combat capability: Through close communication and collaborative work with the UAV flight control system and ground control station, it can respond to mission requirements in real time, cooperate with other combat systems or emergency support systems, exert greater effectiveness, and improve the overall mission execution capability.

[0019] Of course, any product implementing this invention does not necessarily need to achieve all of the technical effects described above at the same time. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a hardware architecture diagram of an unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing hardware device provided in one embodiment of the present invention; Figure 2 This is a software functional unit diagram of an unmanned aerial vehicle (UAV) electromagnetic spectrum sensing hardware device provided in one embodiment of the present invention. Detailed Implementation

[0022] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0024] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0025] This invention provides an unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing device. By integrating multiple functional units, this device achieves comprehensive sensing and analysis of the electromagnetic environment, providing technical support for the safe flight of UAVs in complex electromagnetic environments.

[0026] Step S1: The spectrum sensing antenna array receives wideband electromagnetic signals. The spectrum sensing antenna array uses a combination of multiple antennas to cover different frequency bands and has an adaptive adjustment function to automatically adjust the antenna direction and polarization according to the UAV's flight attitude and electromagnetic environment changes.

[0027] As the signal receiving front end of the entire device, the spectrum sensing antenna array plays a crucial role in capturing various electromagnetic signals in space. This antenna array employs a diversified design concept, combining different types of antennas to achieve full coverage reception of wideband electromagnetic signals. In practical applications, UAVs encounter electromagnetic signals of various frequency bands during missions, including communication signals, radar signals, navigation signals, and various interference signals. The frequency range of these signals can extend from tens of megahertz to tens of gigahertz.

[0028] The design of multi-antenna combinations fully considers the propagation characteristics and reception requirements of signals in different frequency bands. Low-frequency signals typically have strong diffraction capabilities and propagation distances, but their signal power is relatively low, requiring high-gain receiving antennas. High-frequency signals, although having limited propagation distances, have strong information carrying capacity, demanding higher antenna directivity. By rationally configuring different types of antenna elements, effective acquisition of signals in various frequency bands can be achieved while ensuring receiving sensitivity.

[0029] The adaptive adjustment function is the core technical feature of this antenna array. It can dynamically adjust the antenna's operating parameters based on the real-time flight status of the UAV and changes in the surrounding electromagnetic environment. During flight, the UAV undergoes various attitude changes, including climbing, descending, turning, and hovering. These attitude changes directly affect the antenna's pointing and polarization direction, thus affecting signal reception. At the same time, the electromagnetic environment along the UAV's flight path is constantly changing, and the signal strength, interference level, and signal type may vary significantly in different areas.

[0030] In one embodiment, the adaptive adjustment function calculates the actual pointing of the antenna relative to the ground coordinate system by monitoring the UAV's pitch, roll, and yaw angles in real time. When the UAV is performing a reconnaissance mission, if the target area is located to the side or front of the UAV, the system automatically adjusts the pointing of the directional antenna in the antenna array so that its main lobe is aligned with the target area, thereby obtaining the best signal reception effect. At the same time, the system also adjusts the antenna polarization mode according to the polarization characteristics of the target signal to ensure polarization matching and reduce polarization loss.

[0031] Step S11: The multi-element antenna combination includes an omnidirectional antenna and a directional antenna. The omnidirectional antenna is used for low-frequency signal reception, and the directional antenna is used for high-frequency signal reception.

[0032] The omnidirectional antenna in this system is primarily responsible for receiving low-frequency signals. Low-frequency signals typically refer to electromagnetic signals with frequencies ranging from 30 MHz to 1 GHz, including FM radio, television signals, and mobile communication base station signals. The omnidirectional antenna has a 360-degree horizontal radiation pattern, enabling it to receive signals from all directions. This characteristic makes it particularly suitable for applications where the signal direction is uncertain or where simultaneous monitoring of signals from multiple directions is required.

[0033] In UAV applications, this characteristic of omnidirectional antennas is particularly important. When UAVs are performing patrol or reconnaissance missions, they often need to comprehensively monitor the electromagnetic environment within a 360-degree radius, not just from a specific direction. Omnidirectional antennas ensure that regardless of the direction the UAV is flying, it can continuously receive low-frequency signals from the surrounding environment, providing continuous data support for electromagnetic situational awareness.

[0034] Directional antennas are specifically designed for receiving high-frequency signals, typically electromagnetic signals with frequencies above 1 gigahertz, including radar signals, satellite communication signals, and microwave link signals. Directional antennas have high gain and strong directivity, with a main lobe width usually ranging from a few degrees to tens of degrees, effectively suppressing interference signals from other directions and improving the signal-to-noise ratio of the target signal.

[0035] High-frequency signals, due to their higher frequency, experience greater path loss and significant signal power attenuation during propagation. Therefore, high-gain directional antennas are required to ensure sufficient receiving sensitivity. Furthermore, high-frequency signals often carry more information, demanding higher reception quality. The high gain of directional antennas effectively improves the power level of the received signal, while their good directivity helps reduce the impact of multipath interference and co-channel interference.

[0036] Step S12: The adaptive adjustment function obtains the pitch, roll, and yaw angles of the UAV through the built-in inertial measurement unit, and the inertial measurement unit outputs attitude angle data.

[0037] The inertial measurement unit (IMU) is a key sensor component for achieving adaptive antenna adjustment, enabling real-time measurement of the UAV's attitude changes in three-dimensional space. This unit typically integrates a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer, and through multi-sensor fusion technology, it can accurately measure the UAV's pitch, roll, and yaw angles.

[0038] Pitch angle reflects the degree to which the drone's nose tilts up and down relative to the horizontal plane. It is positive when the drone is climbing and negative when it is descending. Roll angle represents the angle of rotation of the drone around its longitudinal axis; it is negative when tilted left and positive when tilted right. Yaw angle describes the rotation of the drone around its vertical axis, that is, the angular deviation of the drone's nose from north.

[0039] In practical applications, the inertial measurement unit (IMU) samples these attitude parameters at high frequencies, typically above 100 Hz, to ensure the capture of rapid attitude changes in the UAV. For example, when a UAV performs evasive maneuvers, its attitude may change drastically in a short period of time; high-frequency attitude measurement ensures that the antenna adjustment system responds to these changes in a timely manner.

[0040] After being filtered and calibrated, the attitude angle data is transmitted to the antenna control system. Based on this attitude information, the control system calculates the actual pointing of the antenna array relative to the ground coordinate system, compares it with the preset target pointing, and generates corresponding adjustment commands. This closed-loop control mechanism ensures that the antenna always maintains optimal reception, unaffected by changes in the UAV's attitude.

[0041] Step S13: The adaptive adjustment function obtains the surrounding electromagnetic signal intensity distribution through the electromagnetic environment monitoring unit, and the electromagnetic environment monitoring unit outputs signal intensity distribution data.

[0042] The electromagnetic environment monitoring unit is another important component of the antenna adaptive adjustment system. It is responsible for monitoring the electromagnetic environment around the UAV in real time. This unit uses broadband spectrum scanning technology to continuously monitor electromagnetic signals within a preset frequency range, acquiring signal strength information for each frequency band and direction.

[0043] Signal strength distribution data includes information in both spatial and frequency dimensions. Spatially, the unit acquires signal strength information in different directions through multiple monitoring antennas or by scanning with the main antenna, forming a spatial distribution map of the electromagnetic environment. In the frequency dimension, the unit subdivides the monitoring frequency bands, acquiring the signal strength levels within each sub-band, thus forming a detailed description of the spectrum occupancy.

[0044] In one embodiment, the electromagnetic environment monitoring unit employs fast spectrum scanning technology, enabling it to scan the entire monitoring frequency band within milliseconds. During the scan, the unit records the signal power level at each frequency point and marks strong signals exceeding a preset threshold. These strong signals may originate from communication base stations, radar systems, or other electronic devices, and their presence can affect the optimal pointing selection of the antenna.

[0045] Signal strength distribution data also includes information on the time-varying characteristics of the signal. Some signals may be continuous, such as broadcast signals and base station signals, while others may be intermittent, such as radar scanning signals and burst communication signals. Through continuous observation, the monitoring unit can identify the time characteristics of these different types of signals, providing more comprehensive information for the formulation of antenna adjustment strategies.

[0046] Step S14: Adjust the antenna orientation and polarization based on the fusion result of attitude angle data and signal strength distribution data.

[0047] Data fusion is the core component for achieving intelligent antenna adjustment. It integrates attitude information from the inertial measurement unit (IMU) and signal distribution information from the electromagnetic environment monitoring unit (EMIC) to generate the optimal antenna adjustment strategy. The fusion algorithm needs to consider multiple factors simultaneously, including the UAV's current attitude, the location of the target signal, the distribution of interference signals, and mission requirements.

[0048] Attitude angle data provides fundamental coordinate transformation information for antenna adjustment. Since the antenna array is fixedly mounted on the UAV body, the actual pointing of the antenna will change accordingly when the UAV's attitude changes. Using the attitude angle data, the system can calculate the antenna's current actual pointing and determine the necessary compensation adjustment to maintain the antenna pointing towards the target direction.

[0049] Signal strength distribution data provides detailed information about the electromagnetic environment for antenna adjustment. In complex electromagnetic environments, multiple strong signal sources may exist simultaneously. The system needs to select the most suitable target signal based on mission requirements and avoid directions of strong interference signals. For example, when a UAV needs to receive communication signals in a specific frequency band, the system will search for the strongest signal direction within that band and point the antenna in that direction.

[0050] Antenna orientation adjustment is achieved through a servo control system, which precisely controls the antenna's azimuth and elevation angles. The azimuth adjustment range is typically 360 degrees, while the elevation adjustment range depends on the antenna type and installation location, generally between -90 degrees and +90 degrees. The adjustment accuracy is typically within 0.1 degrees, ensuring the antenna is accurately pointed towards the target.

[0051] Polarization adjustment is another important optimization technique. Electromagnetic signals have different polarization characteristics, including linear polarization and circular polarization. Maximum received power can be obtained when the antenna polarization matches the signal polarization. The system analyzes the polarization characteristics of the received signal and automatically adjusts the antenna polarization to achieve polarization matching and reduce polarization loss.

[0052] In step S2, the signal conditioning unit performs filtering, amplification, and frequency conversion preprocessing on the electromagnetic signals received by the spectrum sensing antenna array.

[0053] The signal conditioning unit is a crucial bridge connecting the antenna array and the data processing unit. It is responsible for performing necessary preprocessing on the raw electromagnetic signals received by the antenna to meet the requirements of subsequent digital processing. Raw electromagnetic signals typically have a wide spectral range, low signal power, and complex frequency structure, making it difficult to achieve ideal results through direct digital processing.

[0054] Filtering is the first step in signal conditioning, and its main purpose is to remove noise and interference components from the signal and extract the useful signal components. In UAV-borne applications, electromagnetic signals are often affected by various interferences, including pulse interference generated by the engine ignition system, modulation interference caused by rotor rotation, and radiated interference from other electronic devices. If these interferences are not suppressed, they will seriously affect the accuracy of subsequent signal analysis.

[0055] Amplification is used to boost the filtered, weak signal to a power level suitable for subsequent processing. The electromagnetic signal power received by the antenna is typically very small, perhaps only a few microwatts or even less, while analog-to-digital converters and digital signal processors require a certain amplitude input signal to function properly. Low-noise amplification can boost the signal power to a suitable level while maintaining signal quality.

[0056] Frequency conversion is the final step in signal conditioning, converting a wideband radio frequency (RF) signal into a lower-frequency (IF) signal. This frequency conversion simplifies subsequent digital processing, reduces the sampling rate requirements of the analog-to-digital converter (ADC), and facilitates more accurate spectrum analysis.

[0057] Step S21: Filtering is performed by passing through a multi-stage filter to remove interference signals in different frequency bands, resulting in the filtered signal.

[0058] Multistage filter design is a key technology for achieving high-quality signal filtering. Because UAV-borne electromagnetic spectrum sensing equipment needs to process wideband signals, a single filter often cannot simultaneously meet the filtering requirements of different frequency bands. Multistage filters, by cascading multiple filtering units with different characteristics, effectively suppress various interference signals.

[0059] The first-stage filter is typically a broadband bandpass filter. Its main function is to limit the overall frequency range of the signal and filter out interference signals that significantly exceed the frequency band of interest. For example, if the system mainly focuses on signals in the 1 GHz to 6 GHz frequency band, the first-stage filter will filter out signal components below 500 MHz and above 8 GHz to prevent strong interference signals outside these frequency bands from affecting subsequent processing.

[0060] The second-stage filter suppresses specific types of interference. In UAV applications, common interference includes broadband pulse interference from the engine ignition system, switching noise from the motor driver, and clock harmonic interference from digital circuits. These interferences typically have specific spectral characteristics and can be suppressed by designing appropriate notch filters or band-stop filters.

[0061] The third-stage filter performs fine-grained spectrum shaping, further optimizing signal quality. This stage filter typically employs a tunable design, enabling dynamic adjustment of filtering characteristics based on the current signal environment and task requirements. For example, when strong interference is detected in a certain frequency band, the system can automatically adjust the parameters of this stage filter to enhance its ability to suppress interference in that frequency band.

[0062] The filtered signal retains useful information from the original signal while significantly reducing noise and interference levels. The signal-to-noise ratio (SNR) is significantly improved, creating favorable conditions for subsequent amplification and frequency conversion. In one embodiment, after multi-stage filtering, the SNR can be improved by more than 10 dB, effectively improving signal quality.

[0063] Step S22: Amplify the filtered signal using a low-noise amplifier to obtain the amplified signal.

[0064] Low-noise amplifiers are core components in signal conditioning units, requiring them to provide sufficient gain while minimizing noise introduction. In electromagnetic spectrum sensing applications, the dynamic range of signals is vast, encompassing both very weak long-distance signals and strong short-distance signals, which places high demands on amplifier design.

[0065] The gain design of an amplifier requires consideration of multiple factors. Insufficient gain can lead to weak signals being undetectable, while excessive gain can cause strong signals to saturate, resulting in nonlinear distortion. In one embodiment, the system employs a variable gain amplifier design that automatically adjusts the gain based on the strength of the input signal. When the input signal is weak, the system provides a higher gain to ensure effective amplification; when the input signal is strong, the system automatically reduces the gain to prevent amplifier saturation.

[0066] Noise figure is a crucial indicator of the performance of a low-noise amplifier. An excellent low-noise amplifier should have the lowest possible noise figure, typically below 3 dB. To achieve this, various noise suppression techniques are employed in amplifier design, including optimizing transistor operating points, using low-noise components, and designing appropriate input matching networks.

[0067] Linearity is another key performance indicator for amplifiers. In multi-signal environments, amplifier nonlinearity can cause intermodulation distortion, generating spurious signal components and affecting the accuracy of spectrum analysis. High linearity design ensures that the amplifier maintains good linearity throughout its operating range by employing linearization techniques, optimizing bias circuits, and using high-linearity components.

[0068] After amplification, the signal amplitude is increased to a level suitable for subsequent processing, typically between tens of millivolts and a few volts. The spectral characteristics of the signal are well preserved, and the relative relationships between the frequency components remain essentially unchanged, laying the foundation for accurate spectral analysis.

[0069] In step S23, the frequency converter converts the amplified signal into an intermediate frequency signal through the frequency converter circuit, and the intermediate frequency signal is used as the input of the data acquisition and processing unit.

[0070] Frequency conversion circuits achieve frequency conversion from radio frequency (RF) to intermediate frequency (IF), which is a standard technology in modern radio receiving systems. The basic principle of frequency conversion is to use a mixer to mix the input RF signal with the local oscillator signal to generate sum and difference frequency components, and then use a filter to select the desired intermediate frequency component.

[0071] The local oscillator is a core component of the frequency conversion circuit, providing a stable reference frequency signal. The frequency stability of the oscillator directly affects the frequency accuracy of the signal after conversion; therefore, high-stability crystal oscillators or phase-locked loop frequency synthesizers are typically used. In broadband spectrum sensing applications, the system may need to process signals in different frequency bands, requiring the local oscillator to have a wide-range frequency tuning capability.

[0072] The mixer is responsible for mixing the frequencies of the radio frequency (RF) signal and the local oscillator (LO) signal. An ideal mixer should have good linearity, low conversion loss, and high isolation. Linearity ensures that the mixing process does not generate excessive harmonics and intermodulation products, conversion loss affects the overall system gain, and isolation relates to the degree of leakage of the LO signal to the RF terminal.

[0073] Intermediate frequency (IF) filters are used to select the target frequency component after mixing and suppress unwanted image frequencies and other spurious components. The selection of the IF frequency requires consideration of several factors, including image suppression requirements, filter implementation complexity, and ease of subsequent processing. Commonly used IF frequencies include 70 MHz, 140 MHz, and 455 MHz.

[0074] Intermediate frequency (IF) signals offer several advantages over raw radio frequency (RF) signals. First, the lower frequency of IF signals facilitates high-precision filtering and amplification. Second, the relatively narrow bandwidth of IF signals reduces the sampling rate requirements for subsequent analog-to-digital converters (ADCs). Finally, IF processing can utilize mature IF devices and technologies, improving system reliability and performance.

[0075] Step S3: The data acquisition and processing unit integrates an analog-to-digital converter and a digital signal processor to perform digital conversion and spectrum analysis on the preprocessed signal output by the signal conditioning unit to obtain the signal frequency, amplitude and phase parameters.

[0076] The data acquisition and processing unit is the core processing unit of the entire electromagnetic spectrum sensing device. It converts analog intermediate frequency signals into digital signals and extracts various characteristic parameters of the signals through advanced digital signal processing algorithms. The performance of this unit directly determines the spectrum analysis accuracy and signal recognition capability of the entire system.

[0077] Analog-to-digital converters (ADCs) play a crucial role in converting analog signals to digital signals. In electromagnetic spectrum sensing applications, ADCs require characteristics such as high sampling rate, high resolution, and wide dynamic range. The sampling rate determines the highest signal frequency the system can process; according to the Nyquist sampling theorem, the sampling rate should be at least twice the highest frequency of the signal. Resolution affects the system's ability to detect weak signals; higher resolution means that smaller signal variations can be detected.

[0078] Digital signal processors (DSPs) are responsible for performing various complex mathematical operations and analyses on the digitized signals. Modern DSPs typically integrate dedicated mathematical operation units, enabling them to efficiently execute commonly used signal processing algorithms such as Fast Fourier Transform, digital filtering, and correlation operations. The processor's computing power directly affects the system's real-time processing performance and analysis accuracy.

[0079] Spectrum analysis is a core function of the data acquisition and processing unit. It transforms time-domain signals into frequency-domain representations through mathematical transformations, revealing the frequency composition and power distribution of the signal. The results of spectrum analysis provide fundamental data for subsequent advanced processing such as signal identification, modulation analysis, and interference assessment.

[0080] In step S4, the communication control unit establishes a communication link with the UAV flight control system, receives flight status information from the UAV flight control system, and feeds back the spectrum sensing results obtained by the data acquisition and processing unit to the UAV flight control system. At the same time, it receives remote commands through the ground control station to adjust the equipment parameters.

[0081] The communication control unit is a crucial interface for interaction between the UAV-borne electromagnetic spectrum sensing equipment and external systems. It is responsible for enabling efficient information exchange between the equipment, the UAV flight control system, and the ground control station. Through this unit, the equipment can acquire real-time flight status information of the UAV, ensuring close integration of spectrum sensing with flight missions. Simultaneously, this unit feeds back the sensed electromagnetic environment information to the flight control system, supporting UAV flight path planning and mission decision-making. Furthermore, the ground control station can send remote commands through this unit to dynamically adjust the equipment's operating parameters to adapt to different mission requirements and electromagnetic environment changes.

[0082] Establishing a communication link requires ensuring the real-time performance and reliability of data transmission. During UAV missions, flight status information and spectrum sensing results need to be exchanged within a short period to ensure the system can respond promptly to environmental changes. The communication control unit typically employs high-bandwidth, low-latency communication protocols to ensure no significant delays or packet loss occur during data transmission. This efficient communication mechanism enables the device to form a closed-loop control system with the flight control system, allowing for real-time adjustments to its operational status.

[0083] Receiving remote commands is another crucial function of the communication control unit. As the mission command center, the ground control station needs to dynamically adjust the operating parameters of the UAV-borne equipment based on mission objectives and the real-time battlefield environment. These commands may involve changes to the spectrum scanning range, adjustments to sensing accuracy, or switching of antenna operating modes. Through remote commands, ground operators can flexibly control the equipment's operation, enabling it to better serve the current mission.

[0084] Step S41: Flight status information includes the UAV's position, speed, and altitude. The communication link uses a wireless communication interface to transmit flight status information.

[0085] Flight status information is crucial data provided by the UAV flight control system, including the UAV's position coordinates in three-dimensional space, flight speed, and current altitude. This information is essential for the operation of electromagnetic spectrum sensing equipment because the UAV's position and attitude directly affect the reception of electromagnetic signals and the results of spectrum analysis. For example, when the UAV is at a high altitude, the signal propagation path is longer, potentially allowing signals to be received from a greater distance; while at low altitudes, terrain obstruction may weaken the signal strength.

[0086] Location information is typically expressed in latitude, longitude, and altitude, accurate to the meter or even sub-meter level. Speed ​​information includes horizontal and vertical speeds, reflecting the drone's motion. Altitude information is divided into relative altitude and absolute altitude; relative altitude refers to the drone's vertical distance from its takeoff point, while absolute altitude refers to its vertical distance from sea level. This information is collected in real-time by the flight control system's sensors and navigation unit and updated at a fixed frequency.

[0087] Wireless communication interfaces are the primary means of transmitting flight status information. These interfaces typically employ dedicated data link technology, supporting bidirectional communication to ensure rapid information transfer between the device and the flight control system. In one embodiment, the wireless communication interface can utilize the UAV's internal communication bus to directly transmit flight status information to the control unit of the spectrum sensing device. This approach reduces the possibility of external interference and improves the stability of data transmission.

[0088] In practical missions, real-time updates of flight status information are crucial for the dynamic adjustment of spectrum sensing. For example, when a UAV rapidly changes its altitude, the device can adjust the antenna's pitch angle based on the altitude change to ensure that the signal reception direction remains aligned with the target area. This dynamic adjustment capability based on flight status enables the device to maintain stable performance in complex flight environments.

[0089] In step S42, the remote command includes the spectrum scanning range and resolution adjustment parameters, and the ground control station sends the remote command via satellite communication.

[0090] Remote commands are a crucial method for ground control stations to remotely operate unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing equipment. These commands cover multiple aspects of equipment operation, with spectrum scanning range and resolution adjustment parameters being the core components. The spectrum scanning range determines the frequency range monitored by the equipment, such as from 1 GHz to 6 GHz, or a wider range. Resolution adjustment parameters affect the accuracy of the equipment's signal frequency analysis; higher resolution allows the equipment to distinguish smaller frequency intervals, but may correspondingly increase processing time.

[0091] The ground control station transmits these remote commands via a satellite communication link. Satellite communication offers wide coverage and long transmission distances, making it particularly suitable for remote control of UAVs operating in remote areas or at sea. Satellite communication links typically employ encryption technology to ensure the security of command transmission and prevent interception or tampering by third parties.

[0092] In one embodiment, the ground control station dynamically adjusts the spectrum scanning range according to mission requirements. For example, when performing a communications signal reconnaissance mission, the control station may limit the scanning range to a specific communications frequency band to improve scanning efficiency and signal acquisition rate. However, when performing a comprehensive electromagnetic environment assessment mission, the scanning range may be extended to a wider frequency band to obtain comprehensive spectrum information. Resolution adjustment parameters are set according to signal complexity, increasing resolution in areas of dense signal to more accurately distinguish different signal sources.

[0093] The reception and execution of remote commands require the equipment to have a rapid response capability. Upon arrival of a command, the communication control unit immediately parses the command content and converts it into specific equipment parameter adjustment commands. This rapid response mechanism ensures that the equipment can flexibly adjust its operating mode according to the real-time needs of ground command during mission execution.

[0094] Step S43: Adjust the adaptive adjustment function parameters of the spectrum sensing antenna array according to the remote command.

[0095] Adaptive adjustment is one of the core features of spectrum-sensing antenna arrays. It can dynamically adjust the antenna's orientation and polarization according to the external environment and mission requirements. Remote commands include parameter adjustments related to adaptive adjustment, such as antenna pointing priority, polarization selection, and sensitivity settings. These parameter adjustments directly affect the antenna's reception of target signals.

[0096] In one possible implementation, the remote command might specify that the antenna should be preferentially pointed in a particular direction. For example, based on intelligence information, the ground control station determines that an important signal source exists in a certain direction and instructs the equipment to adjust the antenna's main lobe direction to that direction. Simultaneously, the command might also specify the antenna's polarization mode. For instance, when the target signal is circularly polarized, the antenna is adjusted to the corresponding circular polarization mode to reduce signal loss caused by polarization mismatch.

[0097] The adjustment process for the adaptive adjustment function parameters is coordinated by the communication control unit. The unit first parses the parameter content in the remote command, and then sends the adjustment command to the antenna control unit. Based on the command, the antenna control unit drives the servo mechanism to adjust the antenna's physical direction, or switches the antenna's polarization mode electronically. After adjustment, the system provides feedback on the result to ensure the command was executed correctly.

[0098] This dynamic adjustment capability based on remote commands enables the equipment to flexibly respond to different mission scenarios. For example, during border patrol missions, the ground control station may frequently adjust the antenna pointing based on real-time intelligence to track the changing location of suspicious signal sources. In this way, the equipment can always maintain optimal reception of target signals, improving the success rate of mission execution.

[0099] Step S5: The data acquisition and processing unit, including the software function unit, performs a spectrum scan, scanning the electromagnetic spectrum according to the preset frequency band range and scanning step size to obtain scanned spectrum data.

[0100] The software functional units within the data acquisition and processing unit are a crucial component for realizing intelligent electromagnetic spectrum sensing. Spectrum scanning is one of the unit's fundamental functions. It uses a systematic scanning method to comprehensively detect the distribution of the electromagnetic spectrum across a preset frequency band. The scanning process proceeds according to the preset frequency band range and scanning step size. The frequency band range determines the frequency interval being scanned, while the scanning step size determines the frequency resolution.

[0101] The choice of frequency band is usually determined by mission requirements. For example, when performing communication signal monitoring missions, the frequency band may be limited to commonly used communication frequency ranges, such as 800 MHz to 2.5 GHz. However, when performing radar signal reconnaissance missions, the frequency band may extend to higher frequency ranges, such as 8 GHz to 12 GHz. The scan step size is set according to the complexity of the signal and resolution requirements; a smaller step size results in a more detailed scan, but also requires more time.

[0102] In one embodiment, the software functional unit supports multi-mode spectrum scanning. The fast scan mode is suitable for scenarios requiring rapid acquisition of a spectrum overview, with a larger scan step size and a shorter time to cover the entire frequency band. The fine scan mode is suitable for scenarios requiring high-precision analysis, with a smaller scan step size, capable of capturing signal components with very small frequency intervals. By switching scan modes, the device can adapt to different task requirements.

[0103] The process of generating scanned spectrum data involves measuring and recording the signal strength at each frequency point. Software functional units control hardware units to stay at each frequency point for a certain period, acquiring signal power data and storing this data as a spectrum distribution map. This spectrum distribution map visually displays the signal strength at different frequencies, providing fundamental information for subsequent signal analysis and environmental assessment.

[0104] In step S51, the software functional unit performs a spectrum scan, scanning the electromagnetic spectrum according to the preset frequency band range and scan step size to obtain scanned spectrum data.

[0105] The specific execution process of spectrum scanning is controlled by a software functional unit. The unit first reads the preset frequency band range and scan step size parameters, and then configures the hardware scanning unit according to these parameters. Under the control of the software, the hardware unit starts from the starting frequency of the frequency band, gradually increases the frequency, and measures the signal strength point by point according to the scan step size until the entire frequency band range is covered.

[0106] During the scanning process, the software functional unit performs preliminary processing on the signal strength data for each frequency point, including noise filtering and data smoothing. Noise filtering is achieved by setting a power threshold, treating signals below the threshold as background noise and eliminating them. Data smoothing reduces the impact of measurement errors and random fluctuations by averaging the signal strength of adjacent frequency points.

[0107] The generation of scanned spectrum data also includes the detection and labeling of signal peaks. The software unit automatically identifies signal peaks in the spectrum that are significantly higher than the background noise and records the frequency location and intensity of these peaks. These signal peaks typically correspond to actual electromagnetic signal sources, providing important clues for subsequent signal classification and feature extraction.

[0108] In one possible implementation, the software functional unit supports dynamic adjustment of scanning parameters. For example, when a dense signal concentration is detected within a certain frequency band during scanning, the unit automatically reduces the scanning step size to increase resolution and more accurately distinguish different signals. This dynamic adjustment capability enables the device to capture target signals more accurately in complex electromagnetic environments.

[0109] In step S52, the software functional unit establishes an electromagnetic signal feature database, compares the scanned spectrum data with the electromagnetic signal feature database, and determines the signal classification result.

[0110] The electromagnetic signal feature database is a fundamental tool for signal classification in software functional units. It stores feature information of various known electromagnetic signals, including frequency range, modulation method, bandwidth characteristics, and time characteristics. This feature information is obtained through historical data accumulation and expert annotation, covering a variety of common types such as communication signals, radar signals, navigation signals, and interference signals.

[0111] The software functional unit compares the scanned spectrum data with feature information in the database, determining the signal type corresponding to each signal peak through feature matching. The comparison process mainly focuses on key features such as the signal's frequency location, intensity distribution, and bandwidth. For example, if the frequency of a signal peak is within a known mobile communication frequency band and its bandwidth matches the characteristics of a typical communication signal, then the signal may be classified as a mobile communication signal.

[0112] In one embodiment, the software functional unit employs a multi-dimensional feature comparison method to improve classification accuracy. In addition to frequency and bandwidth characteristics, the unit also analyzes the signal's modulation characteristics, such as determining whether it is a frequency-modulated or phase-modulated signal by detecting periodic changes in the signal. Furthermore, the unit combines the signal's duration and occurrence pattern to determine whether it is a continuous or bursty signal.

[0113] Signal classification results provide crucial information for subsequent electromagnetic environment assessments and mission decisions. For example, during electronic warfare missions, the equipment can identify enemy radar signals based on the classification results and feed back their location and frequency information to the flight control system to plan evasion paths. In this way, the equipment can help UAVs safely perform missions in complex electromagnetic environments.

[0114] Step S53: The software functional unit calculates electromagnetic environment assessment indicators by combining scanned spectrum data and flight status information. The electromagnetic environment assessment indicators include signal strength distribution and spectrum occupancy rate.

[0115] Electromagnetic environment assessment metrics are important parameters for measuring the complexity of the electromagnetic environment surrounding a drone. They integrate scanned spectrum data and flight status information, reflecting the distribution of signals and the utilization of spectrum resources in the current environment. Signal strength distribution describes the signal power levels in different directions and frequencies, while spectrum occupancy reflects the proportion of a frequency band occupied by signals.

[0116] The calculation process for signal strength distribution first involves grouping the scanned spectrum data according to direction and frequency. Then, statistical analysis is performed on the signal strength within each group to generate an intensity distribution map. This distribution map visually shows which directions and frequency bands have strong signals and which areas have weak signals, providing a reference for antenna pointing adjustment and signal source localization.

[0117] The calculation of spectrum occupancy involves statistically analyzing the frequency points exceeding a preset threshold in the scanned spectrum data and calculating the proportion of these frequency points in the total frequency band. For example, if 30% of the frequency points in the 1 GHz to 2 GHz band contain signals, then the spectrum occupancy of that band is 30%. A high occupancy rate usually indicates a complex electromagnetic environment, with potentially numerous signal sources and interference.

[0118] The introduction of flight status information makes electromagnetic environment assessments more aligned with actual mission requirements. For example, when a UAV is flying at low altitude, terrain obstruction may cause uneven signal strength distribution. The software functional unit will correct the assessment results based on altitude information to ensure the accuracy of the assessment indicators.

[0119] In one possible implementation, the software functional unit generates an environmental situation map based on electromagnetic environment assessment indicators, which is then provided to the ground control station and flight control system for reference. The situation map graphically displays the changing trends of signal strength distribution and spectrum occupancy, helping operators quickly understand the current electromagnetic environment and formulate corresponding mission strategies.

[0120] Step S6, detailed implementation of the adaptive adjustment function.

[0121] Adaptive adjustment is one of the core technologies of spectrum-sensing antenna arrays. It dynamically optimizes the antenna's operating parameters by integrating UAV attitude information and electromagnetic environment information. The following is a detailed description of the specific implementation of this function, covering all aspects of data acquisition, fusion processing, and parameter adjustment.

[0122] In step S61, the inertial measurement unit outputs attitude angle data to the control unit in real time, and the control unit fuses the attitude angle data.

[0123] The inertial measurement unit (IMU) is a crucial sensor component for adaptive adjustment capabilities. It acquires real-time attitude information of the UAV, including pitch, roll, and yaw angles. This angular data is updated at a high frequency, typically hundreds of times per second, ensuring that subtle attitude changes of the UAV during flight can be captured.

[0124] After receiving the attitude angle data, the control unit first filters it to remove errors caused by sensor noise and vibration interference. Following filtering, the control unit fuses the data from different angles to calculate the overall attitude state of the UAV in three-dimensional space. This fusion process considers the mutual influence between different angles; for example, changes in pitch angle may lead to the need for fine-tuning of the roll angle.

[0125] In one embodiment, the control unit employs multi-sensor data fusion technology, combining data from the inertial measurement unit with data from other auxiliary sensors, such as barometric altimeter and GPS data, to further improve the accuracy of attitude estimation. This high-precision attitude information provides a reliable basis for antenna orientation adjustment.

[0126] In step S62, the electromagnetic environment monitoring unit outputs signal intensity distribution data to the control unit in real time, and the control unit integrates the signal intensity distribution data.

[0127] The electromagnetic environment monitoring unit acquires information on the intensity distribution of surrounding electromagnetic signals through broadband scanning and multi-directional monitoring. This information includes signal power levels at different frequencies and in different directions, reflecting the complexity of the current electromagnetic environment and the distribution of signal sources.

[0128] After receiving signal strength distribution data, the control unit performs spatiotemporal fusion processing on it. In the temporal dimension, the control unit smooths the continuously acquired signal strength data to reduce the impact of instantaneous fluctuations and extract long-term signal trends. In the spatial dimension, the control unit integrates signal strength data from different directions to generate a spatial distribution map of the electromagnetic environment.

[0129] The fused signal strength distribution data clearly shows which directions and frequency bands have strong signal sources and which areas have weak signals. Based on this information, the control unit determines the priority of antenna pointing adjustments. For example, if multiple strong signal sources exist in a certain direction, the control unit will prioritize adjusting the antenna pointing in that direction to ensure the reception quality of important signals.

[0130] In step S63, the control unit determines the antenna optimization parameters based on the fused data. The antenna optimization parameters include the direction adjustment value and the polarization mode adjustment value.

[0131] Determining the antenna optimization parameters is the core of the adaptive adjustment function. The control unit calculates the optimal operating parameters of the antenna by combining attitude angle data and signal strength distribution data. The directional adjustment values ​​include the adjustment of the antenna's azimuth and elevation angles, while the polarization adjustment values ​​involve switching the antenna polarization mode, such as switching from linear polarization to circular polarization.

[0132] The calculation process for the orientation adjustment value first determines the antenna's current actual pointing based on attitude angle data, and then determines the direction of the target signal by combining signal strength distribution data. The control unit calculates the angle difference that needs to be adjusted by comparing the current pointing and the target direction, and then converts it into specific servo control commands.

[0133] The polarization adjustment value is determined based on the polarization characteristics information in the signal strength distribution data. The control unit analyzes the polarization characteristics of the target signal to determine whether it is linear, circular, or other types, and then selects a matching polarization mode. If the polarization characteristics of the target signal are unclear, the control unit will try multiple polarization modes, compare the reception effects, and select the mode with the best effect.

[0134] In one possible implementation, the control unit supports a multi-objective optimization strategy. For example, when multiple important signal sources exist, the control unit will adjust the antenna to point at different signal sources in turn according to task priorities, ensuring that each signal source can be effectively monitored. This flexible optimization strategy improves the device's adaptability to complex environments.

[0135] In step S64, the spectrum sensing antenna array is adjusted according to the antenna optimization parameters, and the antenna receives optimized electromagnetic signals after adjustment.

[0136] After the antenna optimization parameters are generated, the control unit sends adjustment commands to the antenna control actuator. The actuator includes hardware components such as servo motors and electronic switches, which can precisely control the antenna's physical orientation and polarization mode. The adjustment process is typically completed in milliseconds, ensuring that the antenna can respond quickly to environmental changes.

[0137] Orientation adjustment is achieved via a servo motor, which drives the antenna to rotate to the specified azimuth and elevation angles according to commands. The adjustment accuracy is typically within 0.1 degrees, ensuring that the antenna main lobe is accurately aligned with the target signal direction. Polarization adjustment is achieved via an electronic switch or an adjustable phaser, for example, by changing the feed phase of the antenna element to switch the antenna's polarization mode.

[0138] The adjusted antenna can receive electromagnetic signals at its optimal state. The optimized reception is reflected in improved signal-to-noise ratio and suppression of interference signals. For example, when the antenna is pointed in the direction of a strong signal, the received power of the target signal may increase several times, while interference signals from other directions are effectively suppressed. This optimized reception capability enables the device to accurately capture target signals in complex electromagnetic environments.

[0139] Step S7, detailed implementation of the digital signal processor.

[0140] A digital signal processor (DSP) is the core computing component of a data acquisition and processing unit, responsible for performing complex mathematical operations and feature extraction on digitized signals. The following is a detailed description of the specific implementation of a DSP, covering aspects such as spectrum calculation, feature extraction, and data storage.

[0141] Step S71: Fast Fourier Transform calculates the spectral components of the digital signal to obtain preliminary spectral data.

[0142] The Fast Fourier Transform (FFT) is a commonly used spectral analysis method in digital signal processors. It converts a time-domain signal into a frequency-domain representation, revealing the signal's frequency composition and power distribution. The implementation of the FFT includes steps such as segmenting the digital signal, windowing, and transform calculation.

[0143] Segmentation divides a continuous digital signal into multiple time segments, each containing a certain number of sampling points. Windowing reduces spectral leakage and improves the accuracy of spectral analysis by applying a window function to each segment. Transformation calculation uses efficient mathematical algorithms to convert the time-domain data into frequency-domain data, generating amplitude and phase information for each frequency point.

[0144] Preliminary spectral data contains information about the power distribution of the signal at different frequencies. Each frequency point corresponds to a frequency value and an amplitude value, with the amplitude value reflecting the signal strength of that frequency component. The preliminary spectral data provides a visual representation of the signal's frequency composition, laying the foundation for subsequent feature extraction and signal recognition.

[0145] In one embodiment, the digital signal processor supports multi-resolution spectral analysis. For example, for a broadband signal, the processor first uses a lower-resolution transform to quickly obtain a spectral overview, and then uses a higher-resolution transform for the frequency band of interest to obtain more detailed spectral information. This multi-resolution analysis method improves processing efficiency while ensuring analysis accuracy.

[0146] Step S72: Extract signal features based on preliminary spectrum data. Signal features include modulation type and bandwidth.

[0147] Signal feature extraction is one of the advanced functions of a digital signal processor (DSP). It identifies the modulation type and bandwidth characteristics of a signal through in-depth analysis of preliminary spectral data. The modulation type reflects the signal's information encoding method; common modulation types include amplitude modulation, frequency modulation, and phase modulation. Bandwidth characteristics reflect the frequency range occupied by the signal and are an important indicator for distinguishing different signal types.

[0148] The modulation type identification process is primarily based on the morphological characteristics of the spectral data. For example, the spectrum of an amplitude-modulated signal typically consists of symmetrical sidebands on both sides of the carrier frequency, while the spectrum of a frequency-modulated signal consists of multiple discrete frequency components. By analyzing these morphological characteristics of the spectrum, the processor can determine the modulation method of the signal.

[0149] The process of extracting bandwidth characteristics involves detecting the frequency range where signal power is concentrated in the spectrum, determining the start and end frequencies of the signal, and calculating the bandwidth value. The bandwidth value is crucial for signal classification; for example, narrowband signals typically correspond to voice communication signals, while wideband signals may correspond to data transmission signals or radar signals.

[0150] In one possible implementation, the digital signal processor combines time-domain and frequency-domain features to improve the accuracy of signal feature extraction. For example, by analyzing the changes in the signal's time-domain envelope, its modulation type can be determined; by detecting the signal's frequency hopping characteristics, it can be determined whether it is a frequency-hopping signal. This multi-dimensional feature extraction method enables the device to accurately identify complex signals.

[0151] Step S73: The data acquisition and processing unit stores the electromagnetic spectrum and signal characteristics.

[0152] Data storage is one of the key functions of the data acquisition and processing unit. It saves the generated electromagnetic spectrum and extracted signal features to a storage medium, providing data support for subsequent analysis and task decision-making. The electromagnetic spectrum graphically displays the frequency and intensity distribution of the signal, while the signal features are stored in structured data format, including information such as frequency, bandwidth, and modulation type.

[0153] Storage procedures typically employ a tiered storage strategy. Short-term data is stored in a cache for real-time analysis and display; long-term data is stored in non-volatile storage media for in-depth analysis and archiving after the task is completed. Stored data usually includes timestamps and location information to allow for subsequent tracking of the time and location of signals.

[0154] In one embodiment, the data acquisition and processing unit supports data compression storage technology. By compressing the spectrum and signal characteristic data, storage space usage is reduced and storage efficiency is improved. For example, for spectrum data, the system only stores frequency points where the signal strength exceeds a preset threshold, ignoring background noise. This compression storage method significantly reduces storage requirements while ensuring data integrity. Example 1:

[0155] I. The hardware architecture of the UAV-borne electromagnetic spectrum sensing hardware device of this invention is as follows: Figure 1 As shown.

[0156] 1. Spectrum sensing antenna array: (1) A multi-antenna combination design is adopted, including but not limited to omnidirectional antennas and directional antennas, to cover different frequency bands and ensure comprehensive reception capability of wideband electromagnetic signals. For example, a loop antenna with high sensitivity is selected for the low frequency band to capture low-frequency electromagnetic signals at long distances, such as long-wave communication and navigation signals; a parabolic directional antenna is equipped for the high frequency band to accurately focus on high-frequency signals, such as radar and satellite communication frequency bands, to improve signal reception gain and enhance the detection capability of weak signals.

[0157] (2) The antenna array has an adaptive adjustment function, which can automatically adjust parameters such as antenna direction and polarization according to the UAV's flight attitude, mission requirements and changes in the electromagnetic environment. Through the built-in inertial measurement unit (IMU) and electromagnetic environment monitoring unit working together, it can sense the UAV's pitch, roll and yaw angles and the distribution of surrounding electromagnetic signal strength in real time, intelligently optimize the antenna receiving performance, and ensure stable and efficient reception of electromagnetic signals under various complex working conditions.

[0158] 2. Signal conditioning unit: (1) Preprocess the received raw electromagnetic signal, including filtering, amplification, frequency conversion and other operations. Design multi-stage filters to effectively filter out interference signals in different frequency bands, such as removing noise interference in industrial frequency bands and intermodulation interference of co-frequency communication signals, and purifying the target electromagnetic signal.

[0159] (2) A low-noise amplifier (LNA) is used to amplify weak signals, improve the signal-to-noise ratio, and provide a high-quality signal source for subsequent digital processing. At the same time, a frequency conversion circuit is provided to convert the received high-frequency signals into medium-frequency or low-frequency signals suitable for subsequent processing, reducing the difficulty of data processing and improving the overall performance of the system.

[0160] 3. Data Acquisition and Processing Unit: (1) The integrated high-speed ADC (analog-to-digital converter) has high sampling rate and high resolution characteristics, which can accurately convert analog signals into digital signals and ensure the integrity and accuracy of electromagnetic spectrum information. For example, the sampling rate can reach several GSPS (gigasamples per second) and the resolution can reach more than 16 bits, which can meet the needs of capturing the subtle features of complex electromagnetic signals.

[0161] (2) Use a high-performance digital signal processor (DSP) or field-programmable gate array (FPGA) as the core processing chip to perform real-time spectrum analysis, feature extraction and other operations on the acquired digital signals. Use advanced signal processing technologies such as fast Fourier transform (FFT) algorithm and wavelet transform to quickly calculate the frequency, amplitude and phase parameters of electromagnetic signals, identify different types of signal modulation methods such as AM, FM and PSK, and construct a detailed electromagnetic spectrum.

[0162] 4. Communication control unit: (1) Establish a stable communication link with the UAV flight control system to receive flight status information of the UAV, such as position, speed, and altitude, and at the same time feed back electromagnetic spectrum sensing results to the flight control system to achieve collaborative work between the two. The communication method can be the UAV's built-in 4G / 5G communication unit, data link, or dedicated wireless communication interface to ensure the real-time performance and reliability of data transmission.

[0163] (2) It has remote control capabilities, and can receive instructions from operators via ground control station or satellite communication to adjust the operating parameters of the equipment, such as spectrum scanning range, resolution, and sensitivity. Operators can optimize the equipment performance in real time according to task requirements to adapt to different electromagnetic monitoring scenarios.

[0164] II. Implementation of the software functions of this invention: The software functional units of the UAV-borne electromagnetic spectrum sensing hardware device of this invention are as follows: Figure 2 As shown.

[0165] 5. Spectrum Scanning and Monitoring: (1) Design an intelligent spectrum scanning algorithm that can automatically perform rapid and comprehensive scanning of the electromagnetic spectrum based on preset parameters such as frequency band range, scanning step size, and dwell time. During the scanning process, the spectrum data is updated in real time, and timely warnings are given for newly emerging signals and changes in signal strength, providing dynamic monitoring information for electromagnetic spectrum management.

[0166] (2) Supports multi-mode scanning, such as continuous scanning, intermittent scanning, and priority scanning of key frequency bands, to meet the monitoring needs of different mission scenarios. For example, in emergency communication support missions, key and high-frequency scanning of commonly used emergency communication frequency bands is carried out to ensure smooth communication at critical moments; in military reconnaissance missions, a covert intermittent scanning mode is adopted to avoid being detected by the enemy, while accurately capturing the characteristics of enemy electromagnetic signals.

[0167] 6. Signal recognition and classification: (1) Establish a large electromagnetic signal feature database, covering the feature parameters of various known signals such as civilian communication, military communication, radar, and navigation. Through artificial intelligence algorithms such as machine learning and deep learning, the collected unknown electromagnetic signals are compared with the features in the database to achieve automatic signal identification and classification.

[0168] (2) For unknown signals that cannot be matched with the database, cluster analysis, spectrum template matching and other techniques are used to further explore the signal characteristics, try to infer their possible sources and uses, and provide data support for the study of newly emerging electromagnetic signals.

[0169] 7. Electromagnetic environment assessment: (1) Combining spectrum sensing data with the geographic location information of UAVs, a comprehensive assessment of the electromagnetic environment in the monitoring area is conducted. The assessment indicators include electromagnetic signal strength distribution, spectrum occupancy rate, and interference source location. A detailed electromagnetic environment map is drawn to intuitively display the electromagnetic environment status in the area.

[0170] 8. Data storage and transmission: (1) Equipped with high-capacity storage devices, such as solid-state drives (SSDs), to store the collected electromagnetic spectrum data, signal characteristics, monitoring reports, etc. in real time. The storage format adopts a standardized data format to facilitate subsequent data query, analysis and sharing.

[0171] (2) Optimize the data transmission process. Through technologies such as data compression and packet transmission, utilize the UAV's communication link to transmit important data back to the ground control station or command center in real time. At the same time, it has functions such as breakpoint resume and data verification to ensure the integrity and accuracy of data transmission and prevent data loss.

[0172] III. Specific application scenarios of this invention: 1. Military Application Scenarios – Reconnaissance Missions: In a simulated military exercise, multiple drones equipped with electromagnetic spectrum sensing devices took off in formation and flew towards a pre-designated reconnaissance area. According to the mission plan, the drones approached enemy positions using low-altitude stealth flight. The spectrum sensing antenna arrays of the devices automatically adjusted their direction, aiming at areas where enemy electromagnetic signals might exist, utilizing the combined advantages of omnidirectional and directional antennas to comprehensively receive electromagnetic signals. After the signal conditioning unit filtered, amplified, and frequency-converted the received signals, the data acquisition and processing unit used advanced signal processing algorithms to quickly identify key information such as the enemy's communication frequency bands and radar signal characteristics. A pre-programmed communication control unit then transmitted this intelligence back to our command center in real time. Based on this intelligence, the command center formulated targeted electronic warfare strategies to jam enemy communications, gaining the initiative in the exercise.

[0173] 2. Emergency Medical Services Application Scenario – Emergency Communication Support in Earthquake-Stricken Areas: Following a powerful earthquake, ground communications were largely paralyzed. Emergency response teams swiftly dispatched drones equipped with electromagnetic spectrum sensing devices to the disaster area. Upon takeoff, the drones activated their spectrum scanning function, rapidly searching for usable communication frequencies across the vast disaster zone. After careful scanning, they discovered several unused satellite communication frequencies. The drones then relayed this information to ground-based emergency communication vehicles, which used these frequencies to establish a temporary communication link with rescue teams in the disaster area, enabling information exchange between the command center and the disaster site. Through this temporary link, rescue personnel could promptly report the situation in the disaster area and receive rescue instructions, significantly improving rescue efficiency.

[0174] The foregoing has provided a detailed description of an unmanned aerial vehicle (UAV) electromagnetic spectrum sensing method, device, and readable storage medium according to embodiments of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas; furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

[0175] Certain terms are used in the specification and claims to refer to specific components. Those skilled in the art will understand that hardware manufacturers may use different names to refer to the same component. This specification and claims do not distinguish components based on differences in name, but rather on differences in function. The terms "comprising" and "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising / including but not limited to". "Approximately" means that within an acceptable margin of error, those skilled in the art can solve the technical problem and substantially achieve the technical effect within a certain margin of error. The following descriptions in the specification are preferred embodiments for carrying out this application; however, these descriptions are for the purpose of illustrating the general principles of this application and are not intended to limit the scope of this application. The scope of protection of this application shall be determined by the appended claims.

[0176] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes said element.

[0177] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0178] The foregoing description illustrates and describes several preferred embodiments of this application. However, as previously stated, it should be understood that this application is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the application concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of this application should be within the protection scope of the appended claims.

Claims

1. An unmanned airborne electromagnetic spectrum sensing method, characterized by, The UAV-borne electromagnetic spectrum sensing method includes the following steps: S1: Receives wideband electromagnetic signals through a preset spectrum sensing antenna array. The spectrum sensing antenna array uses a combination of multiple antennas to cover different frequency bands and has an adaptive adjustment function, which automatically adjusts the antenna direction and polarization according to the UAV's flight attitude and changes in the electromagnetic environment. S2: The electromagnetic signals received by the spectrum sensing antenna array are filtered, amplified, and frequency-converted preprocessed by a preset signal conditioning unit; S3: A preset data acquisition and processing unit is established, which integrates an analog-to-digital converter and a digital signal processor. The preprocessed signal output by the signal conditioning unit is digitally converted and subjected to spectrum analysis to obtain the signal frequency, amplitude and phase parameters. S4: The preset communication control unit establishes a communication link with the UAV flight control system, receives the flight status information of the UAV flight control system and feeds back the spectrum sensing results obtained by the data acquisition and processing unit to the UAV flight control system, and at the same time receives remote commands through the ground control station to adjust the equipment parameters.

2. The unmanned airborne electromagnetic spectrum awareness method of claim 1, wherein, S1 specifically includes: The spectrum sensing antenna array is configured as a multi-element antenna combination, which includes an omnidirectional antenna and a directional antenna, wherein the omnidirectional antenna is used for low-frequency signal reception and the directional antenna is used for high-frequency signal reception. The adaptive adjustment function acquires the pitch, roll, and yaw angles of the UAV through the built-in inertial measurement unit, which outputs attitude angle data. The adaptive adjustment function obtains the surrounding electromagnetic signal intensity distribution through the electromagnetic environment monitoring unit, and the electromagnetic environment monitoring unit outputs signal intensity distribution data. The antenna orientation and polarization are adjusted based on the fusion result of the attitude angle data and the signal strength distribution data.

3. The UAV-borne electromagnetic spectrum sensing method according to claim 1, characterized in that, S2 specifically includes: The interference signals in different frequency bands are filtered out by multi-stage filters to obtain the filtered signal; The filtered signal is amplified by a low-noise amplifier to obtain an amplified signal; The amplified signal is converted into an intermediate frequency signal by a frequency conversion circuit, and the intermediate frequency signal is used as the input of the data acquisition and processing unit.

4. The UAV-borne electromagnetic spectrum sensing method according to claim 1, characterized in that, S3 specifically includes: An analog-to-digital converter converts a preprocessed signal into a digital signal, which retains electromagnetic spectrum information. The digital signal processor performs a fast Fourier transform on the digital signal to obtain the signal's frequency, amplitude, and phase parameters; The digital signal processor identifies the signal modulation method based on the signal frequency, amplitude, and phase parameters, and the signal modulation method includes amplitude modulation, frequency modulation, and phase shift keying. The data acquisition and processing unit constructs an electromagnetic spectrum diagram based on the identified signal modulation method, and the electromagnetic spectrum diagram represents the spectrum sensing result.

5. The UAV-borne electromagnetic spectrum sensing method according to claim 1, characterized in that, S4 specifically includes: The system acquires flight status information, including the UAV's position, speed, and altitude, and transmits this flight status information using a wireless communication interface. The ground control station transmits remote commands via satellite communication, which include spectrum scanning range and resolution adjustment parameters. The adaptive adjustment parameters of the spectrum sensing antenna array are adjusted according to the remote command.

6. The UAV-borne electromagnetic spectrum sensing method according to claim 2, characterized in that, The adaptive adjustment in S1 includes: The inertial measurement unit outputs the attitude angle data to the control unit in real time, and the control unit fuses the attitude angle data. The electromagnetic environment monitoring unit outputs the signal strength distribution data to the control unit in real time, and the control unit integrates the signal strength distribution data. The control unit determines antenna optimization parameters based on the fused data, and the antenna optimization parameters include direction adjustment values ​​and polarization mode adjustment values. The spectrum sensing antenna array is adjusted according to the antenna optimization parameters, and the adjusted antenna receives optimized electromagnetic signals.

7. The UAV-borne electromagnetic spectrum sensing method according to claim 4, characterized in that, The digital signal processor in S3 identifies the signal modulation method based on the signal frequency, amplitude, and phase parameters. The signal modulation method includes amplitude modulation, frequency modulation, and phase shift keying, specifically: The Fast Fourier Transform is used to calculate the spectral components of the digital signal to obtain preliminary spectral data; Signal features are extracted based on the preliminary spectrum data, and the signal features include modulation type and bandwidth; The data acquisition and processing unit stores the electromagnetic spectrum and the signal characteristics.

8. The UAV-borne electromagnetic spectrum sensing method according to claim 1, characterized in that, The process by which the digital signal processor in S3 performs a Fast Fourier Transform on the digital signal to obtain the signal frequency, amplitude, and phase parameters specifically includes: Perform a spectrum scan, scanning the electromagnetic spectrum according to the preset frequency band range and scan step size to obtain scanned spectrum data; An electromagnetic signal feature database is established, and the scanned spectrum data is compared with the electromagnetic signal feature database to determine the signal classification result; The electromagnetic environment assessment index is calculated by combining the scanned spectrum data and the flight status information. The electromagnetic environment assessment index includes signal strength distribution and spectrum occupancy rate.

9. An unmanned aerial vehicle (UAV)-borne electromagnetic spectrum sensing device, the UAV-borne electromagnetic spectrum sensing device comprising: At least one processor; The device includes a memory communicatively connected to the at least one processor; characterized in that the memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform the UAV-borne electromagnetic spectrum sensing method as described in any one of claims 1-8.

10. A readable storage medium, characterized in that, The readable storage medium stores a computer program that, when executed, implements the UAV-borne electromagnetic spectrum sensing method as described in any one of claims 1-8.

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