Communication area recognition method and system based on narrow-beam antenna

Abstract

This invention relates to the field of narrow-beam antenna technology, specifically disclosing a communication region identification method and system based on narrow-beam antennas. This invention establishes a background environment baseline by performing low-power pre-scan control on a target narrow-beam antenna; plans a beam direction sequence, performs automatic scanning in each beam direction, and records scanning data from multiple directions; compares the data with the background environment baseline to filter a set of communication directions; determines multiple candidate communication regions; and performs communication testing and region optimization to determine multiple optimized communication regions. This method can establish a background environment baseline, plan a beam direction sequence, perform automatic scanning in each beam direction, compare the data with the background environment baseline to determine multiple candidate communication regions, and perform communication testing and region optimization to determine multiple optimized communication regions, without requiring manual configuration of the communication regions. It enables efficient, stable, and sustainable automatic identification of communication regions.

Description

Technical Field

[0001] This invention belongs to the field of narrow beam antenna technology, and particularly relates to a communication area identification method and system based on narrow beam antennas. Background Technology

[0002] Narrow-beam antennas are a type of antenna that highly concentrates electromagnetic wave energy in the main radiation direction and has a small radiation beam angle. Compared with wide-beam antennas, narrow-beam antennas have higher directivity and greater antenna gain, which can effectively improve the signal propagation distance and reception quality in the target area, while reducing interference to surrounding unrelated areas. They are widely used in satellite communication, radar detection, 5G / 6G mobile communication, millimeter-wave communication, and directional wireless transmission, and are an important basic device for achieving efficient, reliable, low-interference wireless communication and precise spatial perception.

[0003] In existing technologies, the accuracy of communication area identification is generally low, and it often relies on manual configuration of communication areas, which makes it difficult to reflect changes in actual communication conditions, resulting in a lag in area boundary updates. There is a lack of efficient, stable and sustainable communication area identification technologies. Summary of the Invention

[0004] The purpose of this invention is to provide a communication area identification method and system based on a narrow beam antenna, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: A communication area identification method based on narrow beam antennas, the method specifically includes the following steps: Obtain the basic antenna parameters of the target narrow beam antenna, perform low-power pre-scan control on the target narrow beam antenna, analyze environmental noise interference, and establish a background environment baseline. Based on the aforementioned basic antenna parameters, a beam direction sequence is planned. In each beam direction, automatic scanning is performed, and scanning data for multiple directions is recorded. Multiple signal quality features are extracted from the scan data of multiple directions and compared with the background environment baseline to filter the set of communication directions from the beam direction sequence; Continuous analysis and automatic aggregation of the communication direction set are performed to determine multiple candidate communication regions and their corresponding spatial boundary ranges; Based on the multiple spatial boundary ranges, communication tests and region optimizations are performed on the multiple candidate communication regions to determine multiple optimized communication regions.

[0006] A communication area identification system based on a narrow-beam antenna, comprising a background baseline establishment unit, an automatic scanning and recording unit, a communication direction filtering unit, a continuous analysis and aggregation unit, and an area testing and optimization unit, wherein: The background baseline establishment unit is used to acquire the basic antenna parameters of the target narrow beam antenna, perform low-power pre-scan control on the target narrow beam antenna, and perform environmental noise interference analysis to establish a background environment baseline. An automatic scanning and recording unit is used to plan a beam direction sequence according to the basic antenna parameters, perform automatic scanning in each beam direction, and record scanning data in multiple directions. A communication direction filtering unit is used to extract multiple signal quality features from multiple direction scan data, compare them with the background environment baseline, and filter a set of communication directions from the beam direction sequence; The continuous analysis and aggregation unit is used to perform continuous analysis and automatic aggregation on the set of communication directions to determine multiple candidate communication regions and their corresponding spatial boundary ranges. The regional testing and optimization unit is used to perform communication testing and regional optimization on multiple candidate communication regions according to multiple spatial boundary ranges, and determine multiple optimized communication regions.

[0007] Compared with the prior art, the beneficial effects of the present invention are: This invention establishes a background environment baseline by performing low-power pre-scan control on a target narrow-beam antenna; plans a beam direction sequence, performs automatic scanning in each beam direction, and records scanning data in multiple directions; compares the data with the background environment baseline to filter a set of communication directions; determines multiple candidate communication regions; and performs communication testing and region optimization to determine multiple optimized communication regions. This process establishes a background environment baseline, plans a beam direction sequence, performs automatic scanning in each beam direction, compares the data with the background environment baseline to determine multiple candidate communication regions, and performs communication testing and region optimization to determine multiple optimized communication regions. It eliminates the need for manual configuration of communication regions and enables efficient, stable, and sustainable automatic identification of communication regions. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0009] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0010] Figure 2 An application architecture diagram of the system provided in an embodiment of the present invention is shown. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0012] Understandably, in existing technologies, the accuracy of communication area identification is generally low, and it often relies on manual configuration of communication areas, making it difficult to reflect changes in actual communication conditions. This results in a lag in updating area boundaries and a lack of efficient, stable, and sustainable communication area identification technologies.

[0013] To address the aforementioned issues, this invention acquires the basic antenna parameters of the target narrow-beam antenna, performs low-power pre-scan control on the target narrow-beam antenna, analyzes environmental noise interference, and establishes a background environment baseline. Based on the basic antenna parameters, a beam direction sequence is planned, and automatic scanning is performed in each beam direction, recording scan data from multiple directions. Multiple signal quality features are extracted from the scan data and compared with the background environment baseline to filter a set of communication directions from the beam direction sequence. Continuous analysis and automatic aggregation of the communication direction set are performed to determine multiple candidate communication regions and their corresponding spatial boundary ranges. Based on the multiple spatial boundary ranges, communication testing and region optimization are conducted on the multiple candidate communication regions to determine multiple optimized communication regions. This approach enables the establishment of a background environment baseline, the planning of a beam direction sequence, and the automatic scanning in each beam direction, comparing with the background environment baseline to determine multiple candidate communication regions, and conducting communication testing and region optimization to determine multiple optimized communication regions. No manual configuration of communication regions is required, enabling efficient, stable, and sustainable automatic identification of communication regions.

[0014] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0015] Specifically, the communication area identification method based on narrow beam antennas includes the following steps: Step S101: Obtain the basic antenna parameters of the target narrow beam antenna, perform low-power pre-scan control on the target narrow beam antenna, analyze environmental noise interference, and establish a background environment baseline.

[0016] In this embodiment of the invention, a target narrow-beam antenna for which communication area identification is required is determined, and basic antenna parameters such as beamwidth, pointing angle range, scanning step angle, and transmit power of the target narrow-beam antenna are obtained. Then, low-power pre-scan control is performed on the target narrow-beam antenna to obtain pre-scan signal data in each beam direction. Then, statistical analysis of background noise and non-target signals is performed on the pre-scan signal data to establish a background environment baseline, providing a basis for subsequent comparison and judgment.

[0017] In a preferred embodiment of the present invention, the steps of obtaining the basic antenna parameters of the target narrow-beam antenna, performing low-power pre-scan control on the target narrow-beam antenna, and analyzing environmental noise interference to establish a background environmental baseline specifically include the following steps: Step S1011: Determine the target narrow-beam antenna; Step S1012: Obtain the basic antenna parameters of the target narrow beam antenna, including beamwidth, pointing angle range, scanning step angle and transmit power; Step S1013: Perform low-power pre-scan control on the target narrow beam antenna to acquire pre-scan signal data; Step S1014: Perform statistical analysis on the pre-scan signal data for background noise and non-target signals to establish a background environment baseline.

[0018] In a preferred embodiment of the present invention, the step of performing statistical analysis on background noise and non-target signals of the pre-scan signal data to establish a background environment baseline specifically includes the following steps: Step S1014a: Based on the beamwidth and scanning step angle of the target narrow beam antenna, divide the pointing angle range covered by the pre-scan into multiple spatial angle units, and assign a unit identifier to each spatial angle unit.

[0019] The pointing angle range, beamwidth, and scanning step angle are derived from the basic antenna parameters. During partitioning, beamwidth is used as the spatial granularity, and the scanning step angle is used as the partitioning step size, ensuring that each spatial angle element corresponds to one or more pre-scanned beam directions. The resulting set of spatial angle elements and their identifiers serve as spatial indices for subsequent noise analysis.

[0020] Step S1014b: For each spatial angle cell, extract the pre-scan signal sampling sequence received in at least one beam direction covered by the current spatial angle cell from the pre-scan signal data, and construct the sample covariance matrix of the corresponding spatial angle cell based on the extracted pre-scan signal sampling sequence.

[0021] The pre-scan signal data contains a complex baseband sampling sequence for each beam direction. For each spatial angle unit, time-aligned sampling points along its covered beam direction are combined to form a received data matrix; using the received data matrix, the following formula is applied... Calculate the sample covariance matrix R of the current spatial angle cell, where X is the received data matrix, N is the number of sampling snapshots, and H represents the conjugate transpose.

[0022] Step S1014c: Perform eigenvalue decomposition on the sample covariance matrix of each spatial angle unit to obtain an eigenvalue sequence, and identify signal eigenvalues ​​and noise eigenvalues ​​based on the eigenvalue sequence, and use the noise eigenvalues ​​to estimate the local noise power of the current spatial angle unit.

[0023] The sample covariance matrix R is decomposed into eigenvalues, yielding eigenvalues ​​λ1≥λ2≥...≥λM arranged in descending order, where M is the number of array elements or equivalent receiving channels. The number of noise eigenvalues ​​is automatically determined using information theory criteria or eigenvalue gradient detection. The remaining smaller eigenvalues ​​are then classified as noise eigenvalues, and the arithmetic mean of these noise eigenvalues ​​is taken as the local noise power P of the current spatial angle cell. noise .

[0024] Step S1014d: Integrate the local noise power of all spatial angle units to construct a spatial noise power distribution map; at the same time, mark spatial angle units with local noise power higher than a preset dynamic threshold as non-target interference directions, and generate a background environment baseline that includes the spatial noise power distribution map and non-target interference direction markings.

[0025] The preset dynamic threshold is adaptively determined based on the median and standard deviation of the local noise power of all spatial angle units. The spatial noise power distribution map records the mapping relationship between the unit identifier and the local noise power of each spatial angle unit; the non-target interference direction markers clearly indicate the angular range in space where continuous interference exists.

[0026] In this embodiment of the invention, the background environment baseline not only includes noise intensity information, but also incorporates the unique spatial distribution characteristics of narrow beam antennas. This allows interference signals to be accurately identified and eliminated through spatial marking even in complex electromagnetic environments where the interference signals are not stationary in time, thereby ensuring the efficiency and robustness of communication area identification.

[0027] Furthermore, the communication area identification method based on narrow beam antenna also includes the following steps: Step S102: According to the basic antenna parameters, plan the beam direction sequence, perform automatic scanning in each beam direction, and record multiple direction scanning data.

[0028] In this embodiment of the invention, according to the pointing angle range and scanning step angle in the basic antenna parameters, the corresponding beam direction sequence is planned, and then the signals are transmitted one by one according to the multiple beam directions in the beam direction sequence and the corresponding sequence order. The scanning signals of multiple beam directions in the beam direction sequence are received, and the signal strength, time stability and beam direction of the multiple scanning signals are analyzed and recorded to obtain multiple direction scanning data.

[0029] In a preferred embodiment of the present invention, the step of planning a beam direction sequence according to the basic antenna parameters, performing automatic scanning in each beam direction, and recording multiple scanning data specifically includes the following steps: Step S1021: Plan the corresponding beam direction sequence according to the pointing angle range and scanning step angle in the basic antenna parameters; Step S1022: Send signals one by one according to the multiple beam directions in the beam direction sequence; Step S1023: Receive scanning signals for multiple beam directions in the beam direction sequence; Step S1024: Record the signal strength, time stability and beam direction of multiple scanning signals to obtain multiple directional scanning data.

[0030] In a preferred embodiment of the present invention, the step of planning the corresponding beam direction sequence according to the basic antenna parameters and in conjunction with the background environmental baseline specifically includes the following steps: Step S1021a: Generate an initial beam direction sequence that covers the pointing angle range based on the pointing angle range and scanning step angle in the basic antenna parameters.

[0031] The pointing angle range and scanning step angle are derived from the basic antenna parameters. Using the lower limit of the pointing angle range as the starting direction and the scanning step angle as the increment, beam directions are generated sequentially until the upper limit direction is covered, forming an initial beam direction sequence. Each element in the sequence is a beam direction angle value.

[0032] Step S1021b: Extract non-target interference direction markers from the background environment baseline; based on the non-target interference direction markers, identify and mark at least one interference beam direction corresponding to the non-target interference direction in the initial beam direction sequence.

[0033] The background environment baseline includes non-target interference direction markers obtained through spatial angle unit division and eigenvalue analysis. These non-target interference direction markers record the spatial angle range where continuous interference exists. By matching each beam direction in the initial beam direction sequence with the angle range of the non-target interference direction markers, beam directions falling within the angle range are marked as interference beam directions.

[0034] Step S1021c: Set the scanning priority of the interfering beam direction in the initial beam direction sequence to low priority, and adaptively adjust the scanning step of the interfering beam direction to generate an optimized beam direction sequence; wherein, in the optimized beam direction sequence, the original scanning step angle remains uniform between adjacent beam directions, while sparse sampling is performed at the interfering beam direction at an integer multiple of the original scanning step angle, or it is skipped directly. If it is selected to skip directly, the number of skipped beam directions is recorded in the index of the optimized beam direction sequence.

[0035] Specifically, for continuous non-target interference direction marking ranges, sparse sampling points are set at integer multiples of the original scanning step angle of not less than 2, or the non-target interference direction marking ranges are completely skipped; all effective beam directions after adjustment are arranged in sequence, and the skipped direction information is recorded in the sequence metadata.

[0036] In this embodiment of the invention, through the above adaptive planning, the beam direction sequence significantly reduces the number of invalid scans of known interference directions while ensuring full coverage, saving scanning time and system resources. At the same time, the spatial noise information in the background environment baseline is directly utilized, avoiding the possibility of misjudging interference as communication direction, making the subsequent extracted multiple direction scan data purer, and thus making the entire communication area identification process more efficient and robust.

[0037] Furthermore, the communication area identification method based on narrow beam antenna also includes the following steps: Step S103: Extract multiple signal quality features from the multiple directional scanning data and compare them with the background environment baseline to filter the communication direction set from the beam direction sequence.

[0038] In this embodiment of the invention, signal quality analysis is performed on scanning data from multiple directions, multiple signal quality features are extracted, and the multiple signal quality features are compared and analyzed based on the background environment baseline. Effective signals and noise interference are automatically distinguished. Multiple effective signals are selected from multiple scanning signals, and then communication directions corresponding to multiple effective signals are selected from multiple beam directions corresponding to the beam direction sequence. Finally, a set of communication directions is constructed based on multiple communication directions.

[0039] In a preferred embodiment of the present invention, the step of extracting multiple signal quality features from the multiple directional scan data and comparing them with the background environment baseline, and then filtering the communication direction set from the beam direction sequence, specifically includes the following steps: Step S1031: Extract multiple signal quality features from the multiple scan data in the multiple directions; Step S1032: Compare the multiple signal quality features with the background environment baseline, and filter multiple valid signals from the multiple scan signals; Step S1033: Select multiple communication directions corresponding to the effective signals from the beam direction sequence; Step S1034: Construct a communication direction set based on the multiple communication directions.

[0040] In a preferred embodiment of the present invention, the step of comparing the plurality of signal quality features with the background environment baseline and selecting a plurality of valid signals from the plurality of scan signals specifically includes the following steps: Step S1032a: Extract the spatial noise power distribution map and the non-target interference direction marker from the background environment baseline; find the corresponding spatial angle unit in the spatial noise power distribution map according to the angle value of each beam direction in the beam direction sequence, and obtain the local noise power of the current spatial angle unit.

[0041] Each signal quality feature is associated with its corresponding beam direction. The spatial noise power distribution map records the mapping relationship between spatial angle unit identifiers and local noise power, and the non-target interference direction markers indicate the angle range where continuous interference is determined to exist.

[0042] Step S1032b: For the currently processed beam direction, first determine whether the currently processed beam direction falls within the interference angle range indicated by the non-target interference direction mark; if yes, the scanning signal corresponding to the currently processed beam direction is directly determined as an invalid signal, and the subsequent comparison is terminated; if no, then step S1032c is executed.

[0043] This judgment operation utilizes the interference direction information pre-identified in the background environment baseline to quickly eliminate known non-target interference from a spatial dimension, preventing interference signals from entering the subsequent effectiveness evaluation and improving screening efficiency.

[0044] Step S1032c: Calculate the dynamic effective signal determination threshold for the current beam direction using local noise power; compare the signal strength feature in the signal quality features corresponding to the current beam direction with the dynamic effective signal determination threshold, and filter effective signals by combining time stability features.

[0045] The threshold for determining the dynamic valid signal is based on the formula. Calculate, where P noise Here, Δ represents the local noise power of the spatial angle cell corresponding to the current beam direction, and Δ represents the preset signal identification guard interval; both are in dB or dBm. When the signal strength characteristic is greater than the dynamic valid signal determination threshold, and the time stability characteristic meets the preset fluctuation range, the current scan signal is determined to be a valid signal; otherwise, it is determined to be an invalid signal. Each valid signal retains its corresponding beam direction, signal strength, and time stability as the filtering result.

[0046] Step S1032d: Summarize all scan signals that are determined to be valid signals to form a set of valid signals.

[0047] In this embodiment of the invention, by dynamically adapting the judgment threshold in each direction to its local noise environment, weak signals in areas with strong background noise are avoided from being missed, and noise fluctuations in areas with weak noise are prevented from being misjudged as signals. This ensures that the selected effective signals have both high detection probability and low false alarm probability, providing high-quality input for the construction of subsequent communication direction sets, and realizing effective signal screening based on spatial adaptive noise baseline.

[0048] Furthermore, the communication area identification method based on narrow beam antenna also includes the following steps: Step S104: Perform continuous analysis and automatic aggregation on the set of communication directions to determine multiple candidate communication regions and their corresponding spatial boundary ranges.

[0049] In this embodiment of the invention, by analyzing the spatial adjacency relationship and continuous distribution characteristics of the communication direction set, recording the continuous distribution results, and then aggregating the communication directions with spatial continuous distribution in the communication direction set according to the continuous distribution results, multiple candidate communication regions are generated, and the starting and ending directions corresponding to the multiple candidate communication regions are recorded to obtain the spatial boundary range corresponding to the multiple candidate communication regions.

[0050] In a preferred embodiment of the present invention, the step of continuously analyzing and automatically aggregating the set of communication directions to determine multiple candidate communication regions and their corresponding spatial boundary ranges specifically includes the following steps: Step S1041: Perform continuous analysis on the communication direction set and record the continuous distribution results; Step S1042: According to the continuous distribution results, perform candidate continuous aggregation on the communication direction set to generate multiple candidate communication regions; Step S1043: Determine the spatial boundary range corresponding to the multiple candidate communication regions.

[0051] In a preferred embodiment of the present invention, the continuous analysis of the communication direction set and the recording of the continuous distribution results specifically include the following steps: Step S1041a: Sort all communication directions in the communication direction set in ascending order of angle value to form an ordered communication direction sequence; calculate the angle interval between every two adjacent communication directions in the ordered communication direction sequence.

[0052] Each communication direction in the set corresponds to a valid signal and is associated with signal strength characteristics and time stability characteristics. Meanwhile, the background environment baseline includes a spatial noise power distribution map and non-target interference direction markers, and the basic antenna parameters include beamwidth.

[0053] Step S1041b: Traverse the ordered communication direction sequence and divide the sequence into several original continuous segments according to the relationship between the angular interval of adjacent communication directions and the beamwidth; If the angular interval between adjacent communication directions is less than or equal to half of the beamwidth, the adjacent pair is determined to be spatially continuous and assigned to the same original continuous segment; otherwise, it is determined to be a spatial breakpoint, and the original continuous segment division result is generated.

[0054] This step utilizes the spatial coverage characteristics of the beam as the basic criterion for continuity: when the angular interval between adjacent communication directions does not exceed half the beam width, the two beams have significant spatial overlap, and it can be considered that the signals detected are from the same continuous region.

[0055] Step S1041c: For each spatial breakpoint, extract the breakpoint angle range corresponding to the current spatial breakpoint; within the breakpoint angle range, obtain the local noise power of the corresponding spatial angle unit from the spatial noise power distribution map, and extract the signal intensity of each scanning direction within the current breakpoint angle range from the directional scanning data.

[0056] The spatial noise power distribution map is derived from the background environmental baseline. The directional scan data is a record of automatic scanning performed in all planned beam directions; even if some directions are not selected as communication directions, their scan data still exists.

[0057] Step S1041d: If the local noise power within the breakpoint angle range is higher than the preset abnormal noise threshold, and the signal strength exhibits a concave change characteristic of first decreasing and then increasing, then the current spatial breakpoint is determined to be a bridgeable discontinuity, and the original continuous segments on both sides of the current spatial breakpoint are marked as potential mergeable segments; otherwise, it is determined to be a real breakpoint.

[0058] The preset abnormal noise threshold is adaptively determined based on the statistical distribution of spatial noise power in the background environmental baseline. The concave variation characteristic refers to the signal strength in the scanning direction within the breakpoint range continuously decreasing to a minimum on one side and then continuously increasing to the other side, indicating that there may be a minimum value of the signal that is not covered by the communication direction, rather than a truly signal-free area. This judgment utilizes background noise information and signal spatial distribution characteristics to avoid erroneous segmentation caused by missed detection of effective directions due to local strong noise.

[0059] Step S1041e: Summarize the start and end directions of all original continuous segments, the number of communication directions included, and the information of all bridgeable discontinuities and the indexes of potential mergeable segments on both sides to form a continuous distribution result.

[0060] In this embodiment of the invention, the continuous distribution results not only record the basic spatial continuity segments, but also include breakpoint properties and merging suggestions, providing richer decision-making basis for subsequent aggregation. Even if there are transient gaps in the communication direction set caused by noise or interference, they can be identified and marked, thus providing an opportunity to recover the complete communication area spatial range during aggregation.

[0061] Furthermore, the communication area identification method based on narrow beam antenna also includes the following steps: Step S105: According to the multiple spatial boundary ranges, perform communication testing and region optimization on the multiple candidate communication regions to determine multiple optimized communication regions.

[0062] In this embodiment of the invention, communication tests are performed on multiple candidate communication regions according to multiple spatial boundary ranges, the communication test results are recorded, and then signal identification is performed on the communication test results to determine multiple abnormal directions. In the multiple candidate communication regions, abnormal directions are eliminated and optimized to generate multiple optimized communication regions.

[0063] In a preferred embodiment of the present invention, the step of performing communication testing and region optimization on multiple candidate communication regions according to multiple spatial boundary ranges to determine multiple optimized communication regions specifically includes the following steps: Step S1051: Perform communication tests on multiple candidate communication regions according to multiple spatial boundary ranges, and record the communication test results; Step S1052: Based on the communication test results, determine multiple abnormal directions; Step S1053: In the multiple candidate communication regions, multiple abnormal directions are eliminated to generate multiple optimized communication regions.

[0064] In a preferred embodiment of the present invention, determining multiple abnormal directions based on the communication test results specifically includes the following steps: Step S1052a: Extract the test signal strength, test time stability and test bit error rate of all test beam directions in each candidate communication area from the communication test results; The test beam direction is a set of directions used for full coverage testing within the spatial boundary of the candidate communication area, with a scanning step angle.

[0065] The communication test results record various indicators obtained by rescanning between the start and end directions of the candidate communication region using the original scan step. Each test beam direction corresponds to an angle value.

[0066] Step S1052b: For each test beam direction within the candidate communication area being processed, find the local noise power of the spatial angle cell corresponding to the current test beam direction from the spatial noise power distribution map contained in the background environment baseline established in step S1014.

[0067] The spatial noise power distribution map stores the mapping relationship between spatial angle cell identifiers and local noise power. If the test beam direction corresponds exactly to a spatial angle cell, it is directly extracted; if it lies between two cells, its local noise power can be determined using nearest neighbor interpolation. This local noise power reflects the noise floor level measured in that direction during the pre-scanning phase.

[0068] Step S1052c: Calculate the abnormal direction dynamic determination threshold for the current test beam direction using the local noise power; compare the test signal strength with the abnormal direction dynamic determination threshold, and determine whether the current test beam direction is an abnormal direction by combining test time stability and test bit error rate.

[0069] The abnormal direction dynamic determination threshold is based on the formula. The calculation involves setting δ, where δ is a preset anomaly detection tolerance in dB or dBm. If the test signal strength is less than the dynamic anomaly direction determination threshold, or the variance or standard deviation of the test time stability exceeds a preset stability range, or the test bit error rate is higher than a preset bit error rate threshold, then the test beam direction is marked as an anomaly direction. This step uses background noise levels for dynamic threshold setting, avoiding misjudging normal weak signals as anomalies in strong noise environments and preventing performance degradation directions from being overlooked in weak noise environments.

[0070] Step S1052d: Summarize all marked abnormal directions within the current candidate communication area and associate them with the spatial boundary range of the current candidate communication area to form a candidate area abnormal direction mapping table; use the candidate area abnormal direction mapping table as the abnormal direction determination result.

[0071] In this embodiment of the invention, the determination of the abnormal direction is no longer a simple comparison of fixed thresholds, but is closely integrated with the spatial noise baseline established in the pre-scanning stage, realizing a dynamic and refined evaluation of the internal quality of the candidate communication region, and providing precise guidance for subsequent optimization to generate a clean communication region.

[0072] Furthermore, Figure 2 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0073] In another preferred embodiment of the present invention, the communication area identification system based on a narrow beam antenna includes: Background baseline establishment unit 101 is used to obtain the basic antenna parameters of the target narrow beam antenna, perform low-power pre-scan control on the target narrow beam antenna, perform environmental noise interference analysis, and establish a background environment baseline.

[0074] In this embodiment of the invention, the background baseline establishment unit 101 determines the target narrow beam antenna for which communication area identification needs to be performed, and obtains basic antenna parameters such as beamwidth, pointing angle range, scanning step angle and transmit power of the target narrow beam antenna. Then, it performs low-power pre-scan control on the target narrow beam antenna, obtains pre-scan signal data in each beam direction, and then performs statistical analysis on the pre-scan signal data for background noise and non-target signals to establish a background environment baseline, providing a basis for subsequent comparison and judgment.

[0075] The automatic scanning and recording unit 102 is used to plan the beam direction sequence according to the basic antenna parameters, perform automatic scanning in each beam direction, and record scanning data in multiple directions.

[0076] In this embodiment of the invention, the automatic scanning and recording unit 102 plans the corresponding beam direction sequence according to the pointing angle range and scanning step angle in the basic antenna parameters, and then sends signals one by one according to the multiple beam directions in the beam direction sequence and the corresponding sequence order, and receives the scanning signals of multiple beam directions in the beam direction sequence, and analyzes and records the signal strength, time stability and beam direction of the multiple scanning signals to obtain multiple direction scanning data.

[0077] The communication direction filtering unit 103 is used to extract multiple signal quality features from multiple direction scan data, compare them with the background environment baseline, and filter the communication direction set from the beam direction sequence.

[0078] In this embodiment of the invention, the communication direction filtering unit 103 performs signal quality analysis on multiple direction scanning data, extracts multiple signal quality features, and compares and analyzes multiple signal quality features based on the background environment baseline, automatically distinguishes between valid signals and noise interference, filters multiple valid signals from multiple scanning signals, and then filters the communication directions corresponding to multiple valid signals from multiple beam directions corresponding to the beam direction sequence, and then constructs a communication direction set based on multiple communication directions.

[0079] The continuous analysis and aggregation unit 104 is used to perform continuous analysis and automatic aggregation on the set of communication directions to determine multiple candidate communication regions and their corresponding spatial boundary ranges.

[0080] In this embodiment of the invention, the continuous analysis aggregation unit 104 analyzes the spatial adjacency relationship and continuous distribution characteristics of the communication direction set, records the continuous distribution results, and then aggregates the communication directions with spatial continuous distribution in the communication direction set according to the continuous distribution results to generate multiple candidate communication regions. The starting direction and ending direction corresponding to the multiple candidate communication regions are recorded to obtain the spatial boundary range corresponding to the multiple candidate communication regions.

[0081] The area test optimization unit 105 is used to perform communication tests and area optimization on multiple candidate communication areas according to multiple spatial boundary ranges, and determine multiple optimized communication areas.

[0082] In this embodiment of the invention, the regional test optimization unit 105 performs communication tests on multiple candidate communication regions according to multiple spatial boundary ranges, records the communication test results, then performs signal identification on the communication test results, determines multiple abnormal directions, and performs elimination and optimization processing on the abnormal directions in the multiple candidate communication regions to generate multiple optimized communication regions.

[0083] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A communication area identification method based on a narrow-beam antenna, characterized by, The method specifically includes the following steps: Obtain the basic antenna parameters of the target narrow beam antenna, perform low-power pre-scan control on the target narrow beam antenna, analyze environmental noise interference, and establish a background environment baseline. Based on the aforementioned basic antenna parameters, a beam direction sequence is planned. In each beam direction, automatic scanning is performed, and scanning data for multiple directions is recorded. Multiple signal quality features are extracted from the scan data of multiple directions and compared with the background environment baseline to filter the set of communication directions from the beam direction sequence; Continuous analysis and automatic aggregation of the communication direction set are performed to determine multiple candidate communication regions and their corresponding spatial boundary ranges; Based on the multiple spatial boundary ranges, communication tests and region optimizations are performed on the multiple candidate communication regions to determine multiple optimized communication regions.

2. The narrow-beam antenna based communication area identification method according to claim 1, characterized by, The process of acquiring the basic antenna parameters of the target narrow-beam antenna, performing low-power pre-scan control on the target narrow-beam antenna, analyzing environmental noise interference, and establishing a background environmental baseline specifically includes the following steps: Identify the target narrow-beam antenna; Obtain the basic antenna parameters of the target narrow-beam antenna, including beamwidth, pointing angle range, scanning step angle, and transmit power; Low-power pre-scan control is performed on the target narrow-beam antenna to acquire pre-scan signal data; Statistical analysis of background noise and non-target signals is performed on the pre-scan signal data to establish a background environment baseline.

3. The narrow-beam antenna based communication area identification method according to claim 2, characterized by, The statistical analysis of background noise and non-target signals in the pre-scan signal data to establish a background environment baseline specifically includes the following steps: Based on the beamwidth and scanning step angle of the target narrow beam antenna, the pointing angle range covered by the pre-scan is divided into multiple spatial angle units, and a unit identifier is assigned to each spatial angle unit. For each spatial angle cell, extract the pre-scan signal sampling sequence received in at least one beam direction covered by the current spatial angle cell from the pre-scan signal data, and construct the sample covariance matrix of the corresponding spatial angle cell based on the extracted pre-scan signal sampling sequence. The sample covariance matrix of each spatial angle unit is decomposed into eigenvalues ​​to obtain an eigenvalue sequence. Based on the eigenvalue sequence, signal eigenvalues ​​and noise eigenvalues ​​are identified. The local noise power of the current spatial angle unit is estimated using the noise eigenvalues. Integrate the local noise power of all spatial angle units to construct a spatial noise power distribution map; at the same time, mark spatial angle units with local noise power higher than a preset dynamic threshold as non-target interference directions, and generate a background environment baseline that includes the spatial noise power distribution map and non-target interference direction markings.

4. The narrow-beam antenna based communication area identification method according to claim 3, characterized by, The step of planning the beam direction sequence according to the basic antenna parameters, performing automatic scanning in each beam direction, and recording multiple scanning data specifically includes the following steps: Based on the pointing angle range and scanning step angle in the basic antenna parameters, plan the corresponding beam direction sequence; Signals are transmitted one by one according to the multiple beam directions in the beam direction sequence; Receive scanning signals for multiple beam directions in the beam direction sequence; The signal strength, time stability, and beam direction of multiple scanning signals are recorded to obtain scanning data in multiple directions.

5. The narrow-beam antenna based communication area identification method according to claim 4, characterized by, The step of planning the corresponding beam direction sequence according to the basic antenna parameters and in combination with the background environmental baseline specifically includes the following steps: Based on the pointing angle range and scanning step angle in the basic antenna parameters, an initial beam direction sequence with equal intervals covering the pointing angle range is generated; From the background environment baseline, extract non-target interference direction markers; based on the non-target interference direction markers, identify and mark at least one interference beam direction corresponding to the non-target interference direction in the initial beam direction sequence; The scanning priority of the interfering beam direction in the initial beam direction sequence is set to low priority, and the scanning step of the interfering beam direction is adaptively adjusted to generate an optimized beam direction sequence.

6. The narrow-beam antenna based communication area identification method according to claim 5, characterized by, The step of extracting multiple signal quality features from the multiple scanning data from the multiple directions and comparing them with the background environment baseline, and filtering the communication direction set from the beam direction sequence specifically includes the following steps: Multiple signal quality features are extracted from the scan data from the multiple directions described; The signal quality features are compared with the background environment baseline to select multiple valid signals from the multiple scan signals; From the beam direction sequence, select multiple communication directions corresponding to the valid signals; A set of communication directions is constructed based on the multiple communication directions described.

7. The narrow-beam antenna based communication area identification method according to claim 6, characterized by, The step of comparing multiple signal quality features with the background environment baseline and selecting multiple valid signals from multiple scan signals specifically includes the following steps: Extract the spatial noise power distribution map and the non-target interference direction marker from the background environment baseline; find the corresponding spatial angle cell in the spatial noise power distribution map according to the angle value of each beam direction in the beam direction sequence, and obtain the local noise power of the current spatial angle cell; For the current beam direction being processed, first determine whether the current beam direction falls within the interference angle range indicated by the non-target interference direction mark; if so, the scanning signal corresponding to the current beam direction is directly determined as an invalid signal, and the subsequent comparison is terminated; if not, proceed to the next step. Using local noise power, a dynamic effective signal determination threshold is calculated for the current beam direction; the signal strength feature in the signal quality features corresponding to the current beam direction is compared with the dynamic effective signal determination threshold, and effective signals are selected by combining time stability features; All scan signals that are determined to be valid signals are aggregated to form a set of valid signals.

8. The narrow-beam antenna based communication area identification method according to claim 7, characterized by, The step of continuously analyzing and automatically aggregating the set of communication directions to determine multiple candidate communication regions and their corresponding spatial boundary ranges specifically includes the following steps: Perform continuous analysis on the set of communication directions and record the continuous distribution results; Based on the continuous distribution results, candidate continuous aggregation is performed on the communication direction set to generate multiple candidate communication regions; Determine the spatial boundary range corresponding to the multiple candidate communication regions.

9. The communication area identification method based on a narrow beam antenna according to claim 8, characterized in that, Continuous analysis of the communication direction set and recording of the continuous distribution results specifically includes the following steps: Sort all communication directions in the communication direction set in ascending order of their angle values ​​to form an ordered communication direction sequence; calculate the angle interval between every two adjacent communication directions in the ordered communication direction sequence. Traverse the ordered communication direction sequence and divide the sequence into several original continuous segments according to the relationship between the angular interval of adjacent communication directions and the beamwidth; For each spatial breakpoint, extract the breakpoint angle range corresponding to the current spatial breakpoint; within the breakpoint angle range, obtain the local noise power of the corresponding spatial angle unit from the spatial noise power distribution map, and extract the signal strength of each scanning direction within the current breakpoint angle range from the directional scan data; If the local noise power within the breakpoint angle range is higher than the preset abnormal noise threshold, and the signal strength exhibits a concave change characteristic of first decreasing and then increasing, then the current spatial breakpoint is determined to be a bridgeable discontinuity, and the original continuous segments on both sides of the current spatial breakpoint are marked as potential mergeable segments; otherwise, it is determined to be a real breakpoint. The start and end directions of all original continuous segments, the number of communication directions included, and the information of all bridgeable discontinuities and the indexes of potential mergeable segments on both sides are summarized to form a continuous distribution result.

10. The narrow-beam antenna based communication area identification method according to claim 9, characterized by, The step of performing communication testing and region optimization on multiple candidate communication regions according to multiple spatial boundary ranges, and determining multiple optimized communication regions specifically includes the following steps: According to the multiple spatial boundary ranges, communication tests are performed on the multiple candidate communication regions, and the communication test results are recorded. Based on the communication test results, multiple abnormal directions were identified; In the multiple candidate communication regions, multiple abnormal directions are eliminated to generate multiple optimized communication regions.

11. A communication area identification system based on a narrow-beam antenna, the application to the communication area identification method based on a narrow-beam antenna according to claims 1 to 10, characterized in that, The system includes a background baseline establishment unit, an automatic scanning and recording unit, a communication direction filtering unit, a continuous analysis and aggregation unit, and a regional test optimization unit, wherein: The background baseline establishment unit is used to acquire the basic antenna parameters of the target narrow beam antenna, perform low-power pre-scan control on the target narrow beam antenna, and perform environmental noise interference analysis to establish a background environment baseline. An automatic scanning and recording unit is used to plan a beam direction sequence according to the basic antenna parameters, perform automatic scanning in each beam direction, and record scanning data in multiple directions. A communication direction filtering unit is used to extract multiple signal quality features from multiple direction scan data, compare them with the background environment baseline, and filter a set of communication directions from the beam direction sequence; The continuous analysis and aggregation unit is used to perform continuous analysis and automatic aggregation on the set of communication directions to determine multiple candidate communication regions and their corresponding spatial boundary ranges. The regional testing and optimization unit is used to perform communication testing and regional optimization on multiple candidate communication regions according to multiple spatial boundary ranges, and determine multiple optimized communication regions.

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