Big data-based radar communication integrated antenna beam coordination optimization method and system

Abstract

This invention discloses a radar-communication integrated antenna beam coordination optimization method and system based on big data, belonging to the field of radar communication technology. The method includes the following steps: acquiring electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power timing signals during rapid changes in the target scene; expanding these three types of real-time signals under a unified time reference to establish a dynamic characteristic basis reflecting beam response lag; and continuously analyzing the time misalignment relationship between radar echo energy change signals and communication power timing signals based on the established dynamic characteristic basis. This invention restores the master-slave correspondence between radar transmission and echo sampling through time reference unification and timing coordination adjustment, reducing energy misalignment and detection distortion in dynamic scenarios. Furthermore, by allocating communication power in a segmented timing sequence, it achieves staggered release of radar and communication energy, reducing mutual interference and improving the overall sensing and transmission stability in complex electromagnetic environments.

Description

Technical Field

[0001] This invention relates to the field of radar communication technology, and more specifically to a method and system for integrated radar communication antenna beam coordination optimization based on big data. Background Technology

[0002] Big data-driven integrated radar and communication antenna beam coordination optimization refers to the process of jointly modeling and intelligently controlling the dynamic coupling relationship between radar detection beams and communication beams using massive amounts of multi-source electromagnetic environment data, target distribution data, and communication demand data. Its core idea is to extract the collaborative constraint characteristics of radar and communication in spatial, frequency, and temporal dimensions through big data analysis, and to establish a balance model between radar detection accuracy, communication rate, and link stability using multi-objective optimization algorithms. This allows for the coordinated iterative optimization of parameters such as beam pointing, shape, width, and phase weighting of the antenna array. This optimization process achieves adaptive updates of beam parameters through real-time data-driven and feedback mechanisms, enabling interference suppression and resource sharing for radar detection and communication transmission in complex electromagnetic environments. This improves the system's overall perception and communication performance and provides cross-scenario dynamic adaptability.

[0003] The existing technology has the following shortcomings: In complex electromagnetic environments where target scenarios change rapidly, big data-driven beam adaptive algorithms are prone to response lag due to time delays in data acquisition, feature extraction, and parameter updates. When the external electromagnetic environment changes instantaneously, the algorithm still adjusts beam parameters based on old time-series characteristics, causing momentary misalignment of the antenna beam in the spatial energy distribution. This can lead to energy overlap between the radar detection beam and the communication transmission beam in the main lobe region. This energy overlap causes interference coupling in the radar echo signal, masking the echo characteristics and resulting in target echo waveform distortion, increased range measurement errors, and even target identification errors. Simultaneously, the communication link may experience a sharp drop in signal-to-noise ratio and transmission rate fluctuations during beam overlap, affecting system stability and reliability. Consequently, the overall performance of the integrated radar-communication system is severely limited in dynamic scenarios.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for integrated radar and communication antenna beam coordination optimization based on big data, so as to solve the problems in the background art mentioned above.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a radar-communication integrated antenna beam coordination optimization method based on big data, comprising the following steps: Step 1: Collect electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power time-series signals during the rapid change of the target scene. Expand the three types of real-time signals under a unified time reference to establish a dynamic characteristic basis that reflects beam response lag. Step 2: Based on the established dynamic characteristics, continuously analyze the temporal misalignment relationship between the radar echo energy change signal and the communication power timing signal, extract the time boundary of the energy overlap interval, and obtain the instantaneous time window characterizing the main lobe interference trend. Step 3: Based on the obtained instantaneous time window, the update time sequence of the antenna array beam pointing is slightly advanced, and the time range of the energy overlap interval is shifted forward at the transmission control level to generate the energy time distribution result of dynamic avoidance. Step 4: Based on the generated energy time distribution results of dynamic avoidance, the triggering time sequence of the radar echo sampling process is synchronously delayed and adjusted, and the sampling triggering time sequence and the beam pointing update time sequence are realigned on the time axis to restore the master-slave correspondence of energy distribution. Step 5: Based on the restored master-slave correspondence, adaptive segmentation of the communication signal power timing is performed. The power distribution interval is dynamically limited within each radar scanning cycle to form a coordinated balance between the radar detection signal and the communication transmission signal in terms of time and energy, thereby eliminating instantaneous detection distortion caused by beam energy overlap.

[0007] Preferably, the steps of acquiring electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power timing signals during rapid changes in the target scene include: Electromagnetic energy distribution signals are acquired in the target scene. The signals are collected from different directions, different heights and different azimuth angles through multi-point continuous reception. A constant sampling interval is maintained in the time dimension, and the energy values ​​of each sampling point are recorded to form an energy distribution matrix. While acquiring electromagnetic energy distribution signals, the target motion trajectory signals are acquired simultaneously. By monitoring the changes in target echo time delay, the target distance, orientation, and velocity information are recorded. The changes in target position are synchronously labeled with the sampling time of electromagnetic energy distribution signals to form a target motion trajectory sequence. While acquiring electromagnetic energy distribution signals and target motion trajectory signals, the power time series of communication signals is collected in real time. By recording the transmission power, duration, frequency range and timestamp information of the communication signals, a continuous communication power time series is generated. The electromagnetic energy distribution signal, target motion trajectory signal, and communication signal power time series signal are expanded under a unified time reference. The timestamps are aligned with the same time reference source, and the signals are rearranged and combined into a multi-dimensional time dataset, forming a multi-source time series data set corresponding to energy changes, target displacement, and communication power fluctuations on the time axis.

[0008] Preferably, the steps for continuously analyzing the temporal misalignment relationship between radar echo energy variation signals and communication power timing signals based on the established dynamic characteristic foundation include: The radar echo energy change signal and communication power time sequence signal are extracted from the dynamic characteristics, and the two types of signals are expanded point by point under a unified time reference. The radar energy value and communication power value of each time node are arranged to form a continuous time sequence. The radar energy change trajectory and communication power change distribution in the time series are continuously compared to identify the rising, stable and falling trends of the two in different time periods, and the relative time difference between the two on the time axis is determined to judge the energy superposition trend. Based on the time difference distribution obtained from the comparison, the time boundary of the energy overlap interval is extracted. The front boundary is determined when the radar energy rises and the communication power rises, and the back boundary is determined when the radar energy falls and the communication power falls, thus forming a sequence of energy overlap time intervals. Based on the time boundary of the energy overlap interval, the radar energy change rate and the communication power change rate are synchronously compared, and the time segment in which both are enhanced is extracted as the boundary point of the instantaneous time window. The instantaneous time window set of the main lobe interference trend is formed in chronological order.

[0009] Preferably, during the extraction of the instantaneous time window, the synchronous comparison of the radar echo energy change rate and the communication power change rate is carried out under a unified time reference. The boundary points of the time segment are recorded in the order of the time sequence and bound to the corresponding energy values. The intervals of adjacent windows in the instantaneous time window set are smoothly connected according to the time continuity to form a continuous time distribution of the main lobe interference trend.

[0010] Preferably, the step of making a slight advance adjustment to the update time sequence of the antenna array beam pointing based on the obtained instantaneous time window includes: Based on the instantaneous time window, the characteristics of radar echo energy change and communication power change within each time window are analyzed one by one. The time difference between beam pointing update time and energy distribution change is determined by comparing the occurrence times of radar energy peak and communication power peak. Based on the distribution characteristics of the time difference, the update time sequence of the antenna array beam pointing is slightly advanced, the time point of the radar energy peak occurrence is shifted forward by a certain amount of time, and smoothing is performed at the boundary of adjacent time windows to maintain the continuity of the time sequence. The pre-adjusted time series is matched with the energy overlap interval. The forward offset range is determined by comparing the time difference between the radar beam update time before and after the adjustment and the starting point of the energy overlap interval. A time connection relationship is established between multiple instantaneous time windows to form a continuous coverage interval. The offset radar beam update time sequence and communication power time sequence signal are superimposed on the time axis to generate the energy time distribution result of dynamic avoidance, so that the radar energy enhancement interval and the communication power enhancement interval are staggered in time and form an alternating energy time pattern.

[0011] Preferably, during the micro-adjustment of the antenna array beam pointing update time sequence, the advance time is determined according to the proportion of the duration of energy overlap, the advance offset range is set synchronously with the start and end times of the instantaneous time window, and the time connection between adjacent time windows is processed in a smooth transition manner to ensure the continuous avoidance relationship between radar beam energy distribution and communication power changes.

[0012] Preferably, the step of adjusting the synchronization delay of the radar echo sampling process based on the generated energy time distribution results of dynamic avoidance includes: Based on the energy time distribution results of dynamic avoidance, the overall distribution information of radar beam pointing update time sequence and communication power change time sequence is extracted, the time relationship between radar energy release node and communication power gap period is analyzed, and a time comparison table containing beam update time point and energy peak is formed. The trigger time sequence of the radar echo sampling process is located. The sampling trigger time delay range is determined by analyzing the peak position of radar energy release. The sampling trigger time is delayed to the stable range of the main lobe energy distribution to ensure that the sampling process corresponds to the main distribution period of the main lobe energy. The delay range is adjusted synchronously with the beam pointing update time sequence. The sampling trigger time point is formed by extending the time interval backward from the beam update time node as the reference point, and a smooth transition region is established between adjacent update time nodes to maintain the continuity of the time series. The adjusted sampling time sequence is realigned with the beam update time sequence on the time axis. The master-slave relationship between radar energy release and echo sampling is restored through the time correspondence, forming a sampling trigger time sequence that advances synchronously with the beam update time.

[0013] Preferably, the delay of the sampling trigger time is determined based on the duration of the radar energy main lobe distribution, and the time extension is performed with the beam pointing update time node as the reference point. The sampling trigger time point is located in the middle of the radar energy stable range to ensure that the echo sampling corresponds to the balanced distribution range of the main lobe energy, thereby maintaining the synchronous advancement relationship between the radar transmission energy release and the echo sampling trigger on the time axis.

[0014] Preferably, the step of adaptively segmenting and allocating the communication signal power timing based on the recovered master-slave correspondence includes: After restoring the master-slave correspondence of energy distribution, the time axis within each radar scanning cycle is partitioned and expanded to extract the time sequence segments corresponding to the beam update time sequence and the radar echo sampling trigger time sequence, and a time structure including the radar energy release stage and the communication power availability stage is established. Based on the radar energy intensity characteristics in each time segment, the communication signal power time sequence is segmented, and the communication power output is divided into a limiting segment, a releasing segment, and a balancing segment, so that the communication power output exhibits alternating characteristics within the scanning cycle. Combining the temporal pattern of radar energy distribution with the delay characteristics of echo sampling trigger time, time ranges and power thresholds are set for each power allocation segment. In the limiting segment, the upper limit of power is limited; in the releasing segment, the power rise rate and maximum output time are limited; and in the balancing segment, the power stable range is limited to maintain the time connection relationship. Align the time boundaries of each power allocation segment with the beam update time sequence and the radar echo sampling trigger time sequence, and stitch them together to form an energy distribution sequence that coordinates the radar detection signal and the communication transmission signal, achieving dynamic coordination in the time and energy dimensions.

[0015] The radar-communication integrated antenna beam coordination optimization system based on big data includes a dynamic feature construction module, a time misalignment analysis module, a beam advance adjustment module, a sampling synchronization adjustment module, and a power segment allocation module. The dynamic feature construction module collects electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power time-series signals during the rapid change of the target scene. It unfolds the three types of real-time signals under a unified time reference to establish a dynamic feature basis that reflects beam response lag. The time misalignment analysis module, based on the established dynamic characteristics, continuously analyzes the time misalignment relationship between the radar echo energy change signal and the communication power time sequence signal, extracts the time boundary of the energy overlap interval, and obtains the instantaneous time window characterizing the main lobe interference trend. The beam advance adjustment module, combined with the obtained instantaneous time window, makes a slight advance adjustment to the update time sequence of the antenna array beam pointing, shifts the time range of the energy overlap interval in advance at the transmission control level, and generates the energy time distribution result of dynamic avoidance. The sampling synchronization adjustment module, based on the generated energy time distribution results of dynamic avoidance, performs synchronization delay adjustment on the triggering time sequence of the radar echo sampling process, realigns the sampling triggering time sequence with the beam pointing update time sequence on the time axis, and restores the master-slave correspondence of energy distribution. The power segmentation allocation module adaptively segments and allocates the communication signal power timing according to the restored master-slave correspondence, dynamically limiting the power distribution range within each radar scanning cycle, thus forming a coordinated balance between radar detection signals and communication transmission signals in terms of time and energy.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention constructs a dynamic feature base under a unified time reference and introduces an instantaneous time window to coordinate the pre- and post-adjustment of the radar beam pointing update time and the echo sampling trigger time. This allows a stable master-slave correspondence to be re-established between radar transmitted energy and echo sampling on the time axis. This method maintains the temporal consistency of radar energy release and reception processes when the target scene changes rapidly, avoiding energy misalignment and echo characteristic disorder caused by response lag. This effectively suppresses echo waveform distortion and measurement deviation, ensuring the continuity and controllability of the radar detection process in a dynamic electromagnetic environment.

[0017] This invention, based on restoring the master-slave correspondence, segments and limits the timing of communication signal power within the scanning period, causing the communication power output and radar energy release to form a staggered distribution in the time dimension. Through this cooperative balancing method, communication transmission activities are guided to occur during radar energy attenuation or gap periods, thereby reducing the probability of energy superposition within the radar main lobe region. This method can reduce mutual interference between radar and communication without weakening communication continuity, enabling the overall system to maintain stable sensing and transmission capabilities in complex electromagnetic scenarios. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a flowchart of the radar-communication integrated antenna beam cooperative optimization method based on big data according to the present invention.

[0020] Figure 2 This is a schematic diagram of the modules of the radar-communication integrated antenna beam cooperative optimization system based on big data according to the present invention. Detailed Implementation

[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0022] This invention provides, for example Figure 1 The radar-communication integrated antenna beam coordination optimization method shown includes the following steps: Step 1: Collect electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power time-series signals during the rapid change of the target scene. Expand the three types of real-time signals under a unified time reference to establish a dynamic characteristic basis that reflects beam response lag. The specific implementation method for this step is as follows: First, electromagnetic energy distribution signals are acquired in the target scenario. Electromagnetic radiation energy at different directions, heights, and azimuths is collected within a predetermined spatial range using a multi-point continuous reception method. During acquisition, a constant sampling interval is maintained in the time dimension to ensure complete spatial energy distribution information is obtained at each time point. The acquired electromagnetic energy data covers both radar and communication operating frequency bands, and background noise power and interference source energy intensity changes are recorded simultaneously. The energy value of each sampling point is recorded with a microsecond-level time resolution, forming an energy distribution matrix in the spatial dimension to describe the electromagnetic energy state at a specific moment. Continuous recording creates a time-series continuous energy change trajectory, reflecting the energy distribution trend in the spatial domain on the time axis. To ensure the integrity of the spatial distribution, multiple angle directions are selected for simultaneous measurement during acquisition, ensuring that the time-series electromagnetic energy data covers the entire working space.

[0023] Simultaneously, the target's motion trajectory signal is acquired while acquiring electromagnetic energy distribution signals. During the acquisition process, the distance and azimuth information of the target in each time period are recorded by monitoring the change in the echo time delay of the target under radar wave illumination. By continuously monitoring the arrival time change of the target echo signal, the displacement path of the target in the time dimension is obtained. To maintain data consistency, the target position change and the sampling time of the electromagnetic energy distribution signal are synchronously labeled in each sampling period, so that the target motion information can correspond to the electromagnetic energy change information. Each time node contains the target's azimuth, distance, and relative velocity data, forming a set of motion trajectory sequences that can be used to describe the target's dynamic behavior. By continuously acquiring the target position change, the impact of the target on the spatial energy distribution during the entire process from appearance to departure can be reflected, thereby ensuring that the electromagnetic energy change and the target motion change remain synchronously correlated in time.

[0024] During the acquisition of electromagnetic energy distribution signals and target trajectory signals, real-time acquisition of communication signal power timing signals was simultaneously performed. The acquisition process monitored the changes in transmission power at the communication signal transmitter over different time periods, forming a time series of communication power by recording power intensity data in real time. The acquisition scope covered the entire power change process of the communication channel throughout the entire radar scan cycle. Communication signal power data included transmission power value, duration, frequency range, and timestamp information. The instantaneous power value of the communication signal was recorded at each time point, forming a continuous power timing curve. To ensure consistency between communication power changes and the aforementioned sampling process for electromagnetic energy distribution and target trajectory, all communication power sampling points were recorded at the same time intervals, maintaining a consistent sampling structure for the three types of signals on the time axis. The communication power change data reflects changes in communication service load, signal allocation adjustments, and power scheduling behavior, providing a fundamental data source for subsequent analysis of the energy coupling relationship between the radar beam and the communication beam.

[0025] After acquiring the three types of signals, the electromagnetic energy distribution signal, target trajectory signal, and communication power time-series signal are unfolded under a unified time reference. The unfolding process uses the same time reference source as the alignment standard, mapping the timestamps of all types of signals to the same time axis. To achieve unified time reference processing, the three types of acquired signals are rearranged in chronological order, and the electromagnetic energy value, target position parameters, and communication power value at each time point are combined into a multidimensional dataset for the same time slice. During the unfolding process, each set of data is time-synchronized, ensuring a one-to-one correspondence between energy changes, target displacement, and communication power fluctuations at the same time point. This unfolding method forms a multi-source time-series data set covering the entire acquisition period. Then, the unfolded data is continuously stitched together according to the time sequence to generate a dynamic feature base reflecting beam response hysteresis. This dynamic feature base includes information on the spatial distribution of electromagnetic energy over time, the continuous trajectory information of the target in the time series, and the time-dimensional variation characteristics of communication power. Based on this foundation, the dynamic trend of beam energy change and its temporal correspondence with target motion and communication power can be accurately described in subsequent processing, providing a complete time correlation basis for analyzing beam response hysteresis characteristics.

[0026] In this implementation process, the acquisition and deployment sequence of the three types of signals maintains strict temporal consistency. The electromagnetic energy distribution signal provides the basis for energy changes in the target scene, the target motion trajectory signal provides data on changes in motion state, and the communication signal power timing signal provides power change information. The deployment results of these three signals under a unified time reference form a continuous temporal mapping structure, constructing a dynamic characteristic foundation reflecting beam response lag. Through this foundation, the synchronization relationship between electromagnetic energy changes and target motion can be tracked in subsequent steps, and the mutual influence between the radar beam and the communication beam in the time dimension can be analyzed, providing continuous temporal support for beam pointing adjustment and energy allocation. This implementation method, by deploying multi-source signals on the same time axis, establishes a dynamic characteristic foundation that can be used to describe the energy temporal correlation in the radar-communication integration process, providing data correlation conditions and temporal continuity basis for subsequent beam collaborative optimization.

[0027] Step 2: Based on the established dynamic characteristics, continuously analyze the temporal misalignment relationship between the radar echo energy change signal and the communication power timing signal, extract the time boundary of the energy overlap interval, and obtain the instantaneous time window characterizing the main lobe interference trend. The specific implementation method for this step is as follows: Based on the established dynamic features, radar echo energy variation signals and communication power time-series signals are extracted, and both types of signals are expanded point-by-point under a unified time reference. During the expansion process, the radar echo energy values ​​and communication power values ​​corresponding to each time node in the dynamic feature foundation are arranged accordingly, so that the two types of signals form a comparable time series on the same time axis. In the continuous arrangement of the time series, the radar echo energy variation signal reflects the energy intensity distribution of the radar beam in the target scene at different time periods, while the communication power time-series signal reflects the power variation process of the communication beam in the same time period. Through this expansion method based on a unified time reference, the changing trends of the two types of signals on the time axis can be directly correlated, facilitating subsequent analysis of time misalignment relationships. This processing ensures that the synchronous change state of radar energy and communication power can be obtained at any time point, thereby constructing a continuous time data foundation that can be used for subsequent analysis.

[0028] After obtaining the time series of radar echo energy change signals and communication power time series signals, the changing trends of the two types of signals on the time axis are continuously compared and analyzed. During the analysis, the trajectory of radar echo energy change and the time distribution of communication power change are continuously observed to identify the rising, stable, and falling trends of both in different time periods. When the radar echo energy shows an increase in energy over time, and the communication power time series signal also shows an increase in power in the same or adjacent time periods, it indicates that there is an energy superposition trend between the radar beam and the communication beam within that time range. To more accurately reflect the time misalignment relationship, the starting point of radar echo energy change and the starting point of communication power change in each time period are compared one by one to identify the time difference between them. This time difference reflects the time offset characteristics caused by beam response lag. When the time difference appears continuously and shows a progressive characteristic, it indicates that there is a continuous misalignment between radar echo energy change and communication power change, at which point the potential energy overlap range can be preliminarily determined. By comparing continuous time periods, a set of continuous time distribution data containing radar energy change trends, communication power change trends, and their relative time differences can be formed, providing a basis for subsequent extraction of energy overlap intervals.

[0029] After completing the continuous analysis of the time misalignment relationship, the time difference distribution obtained from the aforementioned comparison is further processed to extract the time boundary of the energy overlap interval. During the extraction process, based on the overlap characteristics of the radar echo energy change signal and the communication power time sequence signal on the time axis, the energy change curves of both are boundary-identified in the time dimension. When the rising interval of the radar echo energy and the rising interval of the communication power change intersect on the time axis, the starting time point of the intersection is determined as the front boundary of the energy overlap interval; when the falling interval of the radar echo energy and the falling interval of the communication power change separate again on the time axis, the separation time point is determined as the rear boundary of the energy overlap interval. In this way, the time range of the energy overlap interval can be clearly defined. When extracting the time boundary, each pair of start and end time points is recorded in the form of a time series and bound to the corresponding radar energy value and communication power value to form a time series distribution result reflecting the energy overlap time interval. This result can accurately represent the overlap range and duration of the radar beam and communication beam in time during rapid changes in the target scene, providing a basis for identifying the main lobe interference trend.

[0030] After obtaining the time boundary of the energy overlap interval, instantaneous time windows characterizing the main lobe interference trend are further extracted based on the aforementioned time boundary information. During the extraction process, the rate of change of radar echo energy and the rate of change of communication power in the energy overlap interval are synchronously compared on the time axis to identify time segments in which both simultaneously show energy enhancement. Within these time segments, the energy peak of the radar beam main lobe region and the power peak of the communication beam main lobe are close or adjacent in time, indicating that there is a coupling trend between the radar main lobe and the communication main lobe in both spatial and temporal dimensions. The start and end times of these time segments are used as the boundary points of the instantaneous time windows and arranged sequentially in chronological order to form a set of continuous instantaneous time windows. Each instantaneous time window represents a time segment in which main lobe interference may occur. By arranging the continuous windows, the distribution law of the main lobe interference trend changing over time can be reflected. This instantaneous time window is not only used for advance adjustment of subsequent beam update time, but also provides a timing reference for dynamically avoiding energy overlap.

[0031] Throughout the implementation process, the established dynamic characteristic foundation serves as the temporal support for analyzing the time misalignment relationship between radar echo energy change signals and communication power timing signals. Through continuous comparison under a unified time reference, extraction of overlapping intervals, and construction of instantaneous time windows, the dynamic coupling relationship between the radar beam and the communication beam can be accurately revealed in the time dimension. This specific implementation method achieves a fine description of the temporal differences between energy changes and power distribution, providing a complete temporal basis and data foundation for adjusting the beam update timing sequence and dynamically avoiding energy overlap intervals in subsequent steps.

[0032] Step 3: Based on the obtained instantaneous time window, the update time sequence of the antenna array beam pointing is slightly advanced, and the time range of the energy overlap interval is shifted forward at the transmission control level to generate the energy time distribution result of dynamic avoidance. The specific implementation method for this step is as follows: Based on the obtained instantaneous time windows, the radar echo energy change characteristics and communication power change characteristics corresponding to each time window are analyzed one by one. The instantaneous time window represents a critical period of energy coupling between the radar beam and the communication beam in time; therefore, it is necessary to continuously track the energy change trend within each window during processing. By marking the time nodes of radar echo energy rise and fall within the instantaneous time window, the occurrence time of the radar beam energy peak can be obtained; simultaneously, the rise and fall trends of communication power are marked accordingly to determine the occurrence time of the communication beam power peak. Comparing these two peak times on the time axis, if the radar energy peak occurs later than the communication power peak, it indicates a time lag in radar beam pointing update; if the radar energy peak occurs earlier than the communication power peak, it indicates a delay in communication beam response. This comparison of time differences provides a directional reference for subsequent adjustments to the beam update time sequence, ensuring a higher consistency between the time update of beam pointing and changes in energy distribution.

[0033] After determining the time difference within the instantaneous time window, the update sequence of the antenna array beam pointing is slightly advanced based on the distribution characteristics of the time misalignment. During the adjustment process, the occurrence time of the radar energy peak in each time window is shifted forward by a small amount of time, ensuring that the radar beam completes pointing updates before the communication beam power increases, thus achieving avoidance in the time dimension. The amount of time shift is set periodically according to the identified time difference characteristics, and within each time window, the forward shift value maintains a proportional relationship corresponding to the duration of energy overlap. Through continuous adjustment, the update sequence of the radar beam can be moved forward along the time axis as a whole, allowing the energy distribution of the radar beam to complete spatial positioning before the communication beam power increases. To maintain the continuity of beam pointing updates, the boundary points of adjacent time windows are smoothed during the adjustment process, ensuring that there are no abrupt jumps in the adjusted distribution of the time series. Through this method of slightly advanced adjustment, the antenna array beam completes pointing correction before each energy overlap interval arrives, reducing the concentration of main lobe energy during the overlap period.

[0034] After adjusting the antenna array beam update timing sequence in advance, the adjusted time series is matched with the energy overlap interval to determine the advance offset range at the transmit control level. This process determines the advance offset time interval by comparing the time difference between the radar beam pointing update time and the start time of the energy overlap interval in the time series before and after adjustment. When the adjusted radar beam update time is before the start point of the energy overlap interval, this time difference is used as the advance offset at the transmit control level, and it is recorded separately for each time window. For the continuous distribution of multiple instantaneous time windows, a time connection relationship is established between adjacent windows to make the advance offset interval at the transmit control level form a continuous time coverage range. Through this correspondence, the relative timing relationship between radar beam pointing update and energy overlap can be accurately located on the time axis, thereby achieving overall advance timing at the transmit control level. By executing this advance offset during the transmit control process, the time distribution of radar transmit energy is ensured to complete energy release before the communication beam power rises, avoiding the main lobe energy from coinciding with the communication beam energy in the same time period.

[0035] After determining the forward offset interval at the transmission control level, the offset radar beam update time sequence and communication power time sequence signal are re-superimposed to generate a dynamic avoidance energy time distribution result. During the generation process, the adjusted radar energy change curve and the original communication power change curve are synchronously arranged on the time axis. By comparing their correspondence on the time axis, a new energy time distribution structure is formed. In the new distribution result, the radar energy enhancement interval and the communication power enhancement interval are effectively staggered in time. The peak of radar main lobe energy occurs before the increase in communication power, and the peak of communication power occurs after the decrease in radar energy, thus forming an alternating energy time pattern. This dynamic avoidance energy time distribution result can reflect the coordination relationship between the radar beam and the communication beam in the time dimension, allowing their energy release to avoid each other and reducing energy overlap in the main lobe region. Through continuous time avoidance, the energy balance between radar detection and communication transmission can be maintained throughout the entire target scene change process, ensuring a stable beam pointing update rhythm and communication power output rhythm even when the electromagnetic environment changes rapidly, thereby achieving dynamic coordination between the radar beam and the communication beam on the time axis.

[0036] Throughout the implementation process, the introduction of the instantaneous time window provides a specific time reference for the advance adjustment of the beam update timing sequence. By making a forward offset at the transmit control level, the radar energy distribution avoids the period of enhanced communication power in time, thereby forming a dynamic mode of staggered energy release at the energy allocation level. This specific implementation method achieves dynamic coordination between the antenna array beam pointing update timing sequence and the communication power timing sequence through fine adjustment of the time relationship and continuous mapping of the time sequence. This lays a continuous timing foundation for the subsequent synchronous adjustment of the radar echo sampling time and provides specific technical support for achieving energy temporal avoidance between radar detection and communication transmission.

[0037] Step 4: Based on the generated energy time distribution results of dynamic avoidance, the triggering time sequence of the radar echo sampling process is synchronously delayed and adjusted, and the sampling triggering time sequence and the beam pointing update time sequence are realigned on the time axis to restore the master-slave correspondence of energy distribution. The specific implementation method for this step is as follows: Based on the generated energy time distribution results of dynamic avoidance, the overall time distribution of radar beam pointing update time sequence and communication power change time sequence is extracted. This dynamic avoidance energy time distribution result includes the temporal alternation characteristics of radar beam energy release and communication power output. By analyzing this distribution point-by-point, the time node for radar beam pointing update completion and the energy gap period after communication power decrease can be clearly identified. By continuously extracting these time nodes, a time reference table is formed, containing beam update time points, energy release peaks, and communication power change trends. This time reference table reflects the alternating relationship between radar energy release and communication power output in the time dimension, providing a reference for delay adjustment of the radar echo sampling trigger time sequence. By observing the continuous distribution of the beam update time sequence on the time axis, the main period of radar energy release and the gap period of communication power output can be clearly identified, providing precise time positioning for subsequent sampling trigger time adjustments.

[0038] After obtaining the distribution characteristics of the beam update time sequence, the trigger time sequence of the radar echo sampling process is initially located. The trigger time sequence of radar echo sampling corresponds to the time node when the radar transmits energy and receives the echo signal. This time sequence directly determines the sampling accuracy and timing synchronization of the echo signal. Due to the slight advance adjustment of the beam update time, to ensure that the radar echo sampling can accurately receive the energy echo after avoidance, the sampling trigger time sequence needs to be delayed accordingly on the time axis. By analyzing the position of the radar energy release peak in the energy time distribution results of dynamic avoidance, it can be determined that the sampling trigger time should be delayed to the stable interval of the energy main lobe distribution. This stable interval is located within the time period after the beam pointing update is completed, where the energy distribution is relatively balanced and the echo signal strength is stable. Triggering sampling within this time period ensures that the echo sampling process corresponds to the main distribution interval of the beam main lobe energy, avoiding misalignment between the sampling trigger time and the energy avoidance interval, thereby ensuring that the sampling signal and the beam pointing update maintain a consistent time relationship.

[0039] After determining the delay range of the radar echo sampling trigger time, this delay range is synchronized with the beam pointing update time sequence. During the adjustment process, the completion time of each time node in the beam update time sequence is marked, and a time interval is extended forward from this time as a reference point to form the corresponding sampling trigger time point. The extended time interval is determined based on the stable duration of the beam energy distribution, ensuring that the sampling trigger point is located in the period when the radar main lobe energy is most balanced. To ensure the continuity of the time sequence, a smooth transition region is established between adjacent beam update time points, so that the sampling trigger time maintains a stable increasing relationship within a continuous time period. Through this synchronized delay adjustment method, a one-to-one pairing relationship is formed between the sampling trigger time sequence and the beam pointing update time sequence on the time axis, thereby restoring the master-slave correspondence characteristic of energy distribution in the time dimension. Under this correspondence, the beam update time, as the dominant time sequence, determines the time point of radar transmission energy release; the sampling trigger time, as the subordinate time sequence, follows the dominant time sequence with a delay, ensuring that the timing relationship between echo sampling and energy distribution remains coordinated.

[0040] After adjusting the synchronization delay of the sampling trigger time sequence, the adjusted sampling time sequence is realigned with the beam update time sequence on the time axis. During the alignment process, each time node of the sampling trigger time sequence is matched with its corresponding beam update time node, using the beam update time sequence as a reference, ensuring a continuous temporal correspondence between the two on the time axis. This realignment restores the master-slave relationship between radar energy release and echo sampling in the time dimension. That is, after the radar beam update is completed, the sampling trigger event occurs at the delayed time point to capture the echo energy distributed in the main lobe direction after avoidance. After time axis alignment, a new sampling trigger time sequence is formed, which advances synchronously with the beam update time sequence. This ensures that the timing adjustment of beam pointing and the timing trigger of echo sampling remain consistent throughout the entire radar-communication integrated operation. This realignment process ensures that the echo signal sampled by the radar receiver completely corresponds to the energy distribution state under the latest pointing direction, avoiding echo signal mismatch due to timing misalignment.

[0041] Throughout the implementation process, the energy temporal distribution results of dynamic avoidance serve as the core basis, providing a precise time reference for adjusting the delay of radar echo sampling trigger time. By synchronizing and realigning the sampling trigger time sequence with the beam update time sequence, the master-slave correspondence of radar energy distribution can be restored in the time dimension, ensuring that the radar echo sampling process strictly follows the update rhythm of the beam direction. Based on this, the radar receiver can complete sampling within the stable range of beam main lobe energy, ensuring the temporal consistency and energy correspondence of the echo signal, providing a timing basis for subsequent improvement of radar detection accuracy and suppression of communication interference. This specific implementation method, through the synchronization delay and realignment of the time sequence, achieves timing coordination between radar beam transmission and echo sampling under dynamic avoidance conditions, enabling the radar-communication integration process to maintain a stable master-slave energy distribution relationship and temporal correlation characteristics in complex electromagnetic environments.

[0042] Step 5: Based on the restored master-slave correspondence, adaptive segmentation and allocation of communication signal power timing are performed. The power distribution interval is dynamically limited within each radar scanning cycle to form a coordinated balance between radar detection signal and communication transmission signal in time and energy, thereby eliminating instantaneous detection distortion caused by beam energy overlap. The specific implementation method for this step is as follows: After restoring the master-slave correspondence of energy distribution, the time axis within each radar scan cycle is partitioned and expanded, and time sequence segments corresponding to the beam update time sequence and radar echo sampling trigger time sequence are extracted. The master-slave correspondence reflects the coordination state of radar transmission and echo sampling in the time dimension. Based on this, a time reference frame is established for communication signal power allocation. By dividing a complete radar scan cycle into time segments, a continuous set of time segments is formed. Each time segment corresponds to a pointing update phase or echo sampling phase of the radar beam. Arranging these time segments clarifies the distribution period of the radar energy main lobe and the gap period of energy attenuation. In this way, a time structure containing the radar energy release phase and the communication power availability phase can be established on the time axis. This structure provides a continuous time reference for the segmented allocation of communication signal power, ensuring that the distribution process of communication power strictly follows the time distribution law of the radar scan cycle, and ensuring that the power regulation process remains synchronized with the radar operating state.

[0043] After obtaining the temporal distribution structure within the radar scanning cycle, the communication signal power time series is initially segmented based on the radar energy intensity characteristics of each time interval. During segmentation, the continuous time series of communication signal power is divided into multiple power allocation segments based on the changing trend of the radar main lobe energy. In the radar energy peak range, the communication power time series is divided into a limiting segment, during which the communication power output remains at a low level to avoid energy superposition with the radar main lobe. In the radar energy attenuation range, the communication power time series is divided into a releasing segment, during which the communication power can increase within an allowable range, thus fully utilizing the radar energy gap for communication transmission. In the transition range of radar beam repositioning, the communication power is divided into a balancing segment to achieve a continuous transition in power output, ensuring that changes in communication power do not disturb the radar energy distribution. This segmentation method ensures that the communication power output exhibits alternating characteristics of limiting, balancing, and releasing in chronological order within each radar scanning cycle. This segmentation structure guarantees reduced interference during the concentrated release phase of radar energy while fully utilizing communication transmission capabilities during the energy gap phase.

[0044] After forming a segmented structure for the communication signal power, the power output range of each segment is dynamically limited. During this limitation process, the time range and power threshold for each power allocation segment are set based on the temporal pattern of radar energy distribution and the delay characteristics of echo sampling trigger time. In the limiting segment, a power upper limit is set to keep the communication power below the radar main lobe energy threshold, ensuring minimal signal interference at the radar receiver during sampling. In the releasing segment, the power rise rate and maximum output time are set to fully allocate communication energy during radar energy decay periods. In the balancing segment, a stable power range is set to maintain the temporal connection between communication output and radar energy changes. This dynamic limitation method ensures that the communication power output maintains a temporal distribution synchronized with radar energy changes throughout the entire radar scan cycle. The limitation range of each power allocation segment is adjusted in real time according to the recovered master-slave correspondence to ensure that radar energy and communication energy do not overlap on the time axis. This dynamic limitation process creates a staggered energy distribution in the time dimension, enabling radar detection and communication transmission to achieve energy avoidance and time coordination within the same frequency band, thereby forming a stable energy distribution order.

[0045] After completing the power segmentation and dynamic limitation of the communication signal, the allocation results are continuously stitched together throughout the entire radar scanning cycle to generate a coordinated balanced energy distribution sequence of the radar detection signal and the communication transmission signal. During the stitching process, the time boundary of each power allocation segment is aligned one by one with the radar beam update time sequence and the echo sampling trigger time sequence, so that the rising, stabilizing, and falling phases of communication power correspond to the strengthening, stabilizing, and attenuating phases of radar energy in a time-interleaved manner. Under this correspondence, the energy release of the radar detection signal is in the low amplitude range of the communication power, and the energy output of the communication signal is in the radar energy attenuation range, thus forming an alternating energy structure on the time axis. Through this coordinated balance, the radar and communication achieve dynamic coordination in both time and energy dimensions. The energy distribution in the radar main lobe region no longer overlaps with the communication power peak, the radar echo signal can maintain waveform integrity and energy consistency at the receiving end, and the communication link maintains stable data transmission capability during the radar energy release gaps. This coordinated equilibrium state achieves complementary allocation of energy resources through continuous time regulation, fundamentally eliminating instantaneous detection distortion caused by beam energy overlap, and enabling the radar-communication integrated system to maintain stable detection accuracy and communication rate in a rapidly changing electromagnetic environment.

[0046] Through the execution of the above steps, the master-slave correspondence serves as a time reference throughout all stages of power allocation. By adaptively segmenting and dynamically limiting the timing of communication signal power, the communication power output and radar energy release are coordinated in time. This specific implementation method, through continuous regulation at three levels—segmentation, limitation, and balancing—forms a coordinated energy timing relationship within the radar scanning cycle. This provides continuous dynamic support for the time-energy balance between radar detection signals and communication transmission signals, ensuring the integrity of the radar detection beam and the timing stability of communication transmission. It achieves time coupling optimization and coordinated energy release in the integrated radar-communication process.

[0047] Beneficial effect 1: This invention constructs a dynamic feature base under a unified time reference and introduces an instantaneous time window to coordinate the pre- and post-adjustment of the radar beam pointing update time and the echo sampling trigger time. This allows a stable master-slave correspondence to be re-established between radar transmitted energy and echo sampling on the time axis. This method maintains the temporal consistency of radar energy release and reception processes when the target scene changes rapidly, avoiding energy misalignment and echo characteristic disorder caused by response lag. This effectively suppresses echo waveform distortion and measurement deviation, ensuring the continuity and controllability of the radar detection process in a dynamic electromagnetic environment.

[0048] Benefit 2: This invention, based on restoring the master-slave correspondence, segments and limits the timing of communication signal power within the scanning period, causing the communication power output and radar energy release to form a staggered distribution in the time dimension. Through this cooperative balancing method, communication transmission activities are guided to occur during radar energy attenuation or gap periods, thereby reducing the probability of energy superposition within the radar main lobe region. This method can reduce mutual interference between radar and communication without weakening communication continuity, enabling the overall system to maintain stable sensing and transmission capabilities in complex electromagnetic scenarios.

[0049] This invention provides, for example Figure 2 The radar-communication integrated antenna beam coordination optimization system shown includes a dynamic feature construction module, a time misalignment analysis module, a beam advance adjustment module, a sampling synchronization adjustment module, and a power segment allocation module. The dynamic feature construction module collects electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power time-series signals during the rapid change of the target scene. It unfolds the three types of real-time signals under a unified time reference to establish a dynamic feature basis that reflects beam response lag. The time misalignment analysis module, based on the established dynamic characteristics, continuously analyzes the time misalignment relationship between the radar echo energy change signal and the communication power time sequence signal, extracts the time boundary of the energy overlap interval, and obtains the instantaneous time window characterizing the main lobe interference trend. The beam advance adjustment module, combined with the obtained instantaneous time window, makes a slight advance adjustment to the update time sequence of the antenna array beam pointing, shifts the time range of the energy overlap interval in advance at the transmission control level, and generates the energy time distribution result of dynamic avoidance. The sampling synchronization adjustment module, based on the generated energy time distribution results of dynamic avoidance, performs synchronization delay adjustment on the triggering time sequence of the radar echo sampling process, realigns the sampling triggering time sequence with the beam pointing update time sequence on the time axis, and restores the master-slave correspondence of energy distribution. The power segmentation allocation module adaptively segments and allocates the communication signal power timing according to the restored master-slave correspondence, dynamically limiting the power distribution range within each radar scanning cycle, thus forming a coordinated balance between radar detection signals and communication transmission signals in terms of time and energy.

[0050] The radar-communication integrated antenna beam coordination optimization method based on big data provided in this embodiment of the invention is implemented through the aforementioned radar-communication integrated antenna beam coordination optimization system based on big data. For details of the specific methods and processes of the radar-communication integrated antenna beam coordination optimization system based on big data, please refer to the embodiments of the radar-communication integrated antenna beam coordination optimization method based on big data, which will not be repeated here.

[0051] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A radar-communication integrated antenna beam coordination optimization method based on big data, characterized in that, Includes the following steps: Step 1: Collect electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power time-series signals during the rapid change of the target scene. Expand the three types of real-time signals under a unified time reference to establish a dynamic characteristic basis that reflects beam response lag. Step 2: Based on the established dynamic characteristics, continuously analyze the temporal misalignment relationship between the radar echo energy change signal and the communication power timing signal, extract the time boundary of the energy overlap interval, and obtain the instantaneous time window characterizing the main lobe interference trend. Step 3: Based on the obtained instantaneous time window, the update time sequence of the antenna array beam pointing is slightly advanced, and the time range of the energy overlap interval is shifted forward at the transmission control level to generate the energy time distribution result of dynamic avoidance. Step 4: Based on the generated energy time distribution results of dynamic avoidance, the triggering time sequence of the radar echo sampling process is synchronously delayed and adjusted, and the sampling triggering time sequence and the beam pointing update time sequence are realigned on the time axis to restore the master-slave correspondence of energy distribution. Step 5: Based on the restored master-slave correspondence, adaptive segmentation of the communication signal power timing is performed, and the power distribution interval is dynamically limited within each radar scanning cycle to form a coordinated balance between radar detection signal and communication transmission signal in terms of time and energy.

2. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 1, characterized in that, The steps for acquiring electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power timing signals during a rapidly changing target scene include: Electromagnetic energy distribution signals are acquired in the target scene. The signals are collected from different directions, different heights and different azimuth angles through multi-point continuous reception. A constant sampling interval is maintained in the time dimension, and the energy values ​​of each sampling point are recorded to form an energy distribution matrix. While acquiring electromagnetic energy distribution signals, the target motion trajectory signals are acquired simultaneously. By monitoring the changes in target echo time delay, the target distance, orientation, and velocity information are recorded. The changes in target position are synchronously labeled with the sampling time of electromagnetic energy distribution signals to form a target motion trajectory sequence. While acquiring electromagnetic energy distribution signals and target motion trajectory signals, the power time series of communication signals is collected in real time. By recording the transmission power, duration, frequency range and timestamp information of the communication signals, a continuous communication power time series is generated. The electromagnetic energy distribution signal, target motion trajectory signal, and communication signal power time series signal are expanded under a unified time reference. The timestamps are aligned with the same time reference source, and the signals are rearranged and combined into a multi-dimensional time dataset, forming a multi-source time series data set corresponding to energy changes, target displacement, and communication power fluctuations on the time axis.

3. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 1, characterized in that, The steps for continuously analyzing the time misalignment relationship between radar echo energy variation signals and communication power timing signals based on the established dynamic characteristics include: The radar echo energy change signal and communication power time sequence signal are extracted from the dynamic characteristics, and the two types of signals are expanded point by point under a unified time reference. The radar energy value and communication power value of each time node are arranged to form a continuous time sequence. The radar energy change trajectory and communication power change distribution in the time series are continuously compared to identify the rising, stable and falling trends of the two in different time periods, and the relative time difference between the two on the time axis is determined to judge the energy superposition trend. Based on the time difference distribution obtained from the comparison, the time boundary of the energy overlap interval is extracted. The front boundary is determined when the radar energy rises and the communication power rises, and the back boundary is determined when the radar energy falls and the communication power falls, thus forming a sequence of energy overlap time intervals. Based on the time boundary of the energy overlap interval, the radar energy change rate and the communication power change rate are synchronously compared, and the time segment in which both are enhanced is extracted as the boundary point of the instantaneous time window. The instantaneous time window set of the main lobe interference trend is formed in chronological order.

4. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 3, characterized in that, During the extraction of instantaneous time windows, the synchronous comparison of the radar echo energy change rate and the communication power change rate is carried out under a unified time reference. The boundary points of the time segment are recorded in the order of time sequence and bound to the corresponding energy values. The intervals of adjacent windows in the instantaneous time window set are smoothly connected according to the time continuity to form a continuous time distribution of the main lobe interference trend.

5. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 3, characterized in that, The steps for making slight advance adjustments to the update time sequence of the antenna array beam pointing based on the obtained instantaneous time window include: Based on the instantaneous time window, the characteristics of radar echo energy change and communication power change within each time window are analyzed one by one. The time difference between beam pointing update time and energy distribution change is determined by comparing the occurrence times of radar energy peak and communication power peak. Based on the distribution characteristics of the time difference, the update time sequence of the antenna array beam pointing is slightly advanced, the time point of the radar energy peak occurrence is shifted forward by a certain amount of time, and smoothing is performed at the boundary of adjacent time windows. The pre-adjusted time series is matched with the energy overlap interval. The forward offset range is determined by comparing the time difference between the radar beam update time before and after the adjustment and the starting point of the energy overlap interval. A time connection relationship is established between multiple instantaneous time windows to form a continuous coverage interval. The offset radar beam update time sequence and communication power time sequence signal are superimposed on the time axis to generate the energy time distribution result of dynamic avoidance, so that the radar energy enhancement interval and the communication power enhancement interval are staggered in time and form an alternating energy time pattern.

6. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 5, characterized in that, During the micro-adjustment process, the advance time of the antenna array beam pointing update is determined according to the proportion of the duration of energy overlap. The advance offset range is set synchronously with the start and end times of the instantaneous time window, and the time connection between adjacent time windows is handled in a smooth transition manner.

7. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 5, characterized in that, The steps for adjusting the synchronization delay of the radar echo sampling process based on the generated energy time distribution results of dynamic avoidance include: Based on the energy time distribution results of dynamic avoidance, the overall distribution information of radar beam pointing update time sequence and communication power change time sequence is extracted, the time relationship between radar energy release node and communication power gap period is analyzed, and a time comparison table containing beam update time point and energy peak is formed. The trigger time sequence of the radar echo sampling process is located, and the sampling trigger time delay range is determined by analyzing the peak position of radar energy release. The sampling trigger time is then delayed to within the stable range of the energy main lobe distribution. The delay range is synchronized with the beam pointing update time sequence. The sampling trigger time point is formed by extending the time interval backward from the beam update time node as the reference point, and a smooth transition area is established between adjacent update time nodes. The adjusted sampling time sequence is realigned with the beam update time sequence on the time axis. The master-slave relationship between radar energy release and echo sampling is restored through the time correspondence, forming a sampling trigger time sequence that advances synchronously with the beam update time.

8. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 7, characterized in that, The delay of the sampling trigger time is determined based on the duration of the radar energy main lobe distribution, and the time extension is performed with the beam pointing update time node as the reference point. The sampling trigger time point is located in the middle of the radar energy stable range.

9. The radar-communication integrated antenna beam coordination optimization method based on big data according to claim 7, characterized in that, The steps for adaptively segmenting and allocating communication signal power timing based on the recovered master-slave correspondence include: After restoring the master-slave correspondence of energy distribution, the time axis within each radar scanning cycle is partitioned and expanded to extract the time sequence segments corresponding to the beam update time sequence and the radar echo sampling trigger time sequence, and a time structure including the radar energy release stage and the communication power availability stage is established. Based on the radar energy intensity characteristics in each time segment, the communication signal power time sequence is segmented, and the communication power output is divided into a limiting segment, a releasing segment, and a balancing segment, so that the communication power output exhibits alternating characteristics within the scanning cycle. Combining the temporal pattern of radar energy distribution with the delay characteristics of echo sampling trigger time, time ranges and power thresholds are set for each power allocation segment. In the limiting segment, the upper limit of power is limited; in the releasing segment, the power rise rate and maximum output time are limited; and in the balancing segment, the power stable range is limited to maintain the time connection relationship. Align the time boundaries of each power allocation segment with the beam update time sequence and the radar echo sampling trigger time sequence, and stitch them together to form an energy distribution sequence that coordinates the balance between radar detection signals and communication transmission signals.

10. A radar-communication integrated antenna beam coordination optimization system based on big data, used to implement the radar-communication integrated antenna beam coordination optimization method based on big data as described in any one of claims 1-9, characterized in that, It includes a dynamic feature construction module, a time misalignment analysis module, a beam advance adjustment module, a sampling synchronization adjustment module, and a power segmentation allocation module; The dynamic feature construction module collects electromagnetic energy distribution signals, target motion trajectory signals, and communication signal power time-series signals during the rapid change of the target scene. It unfolds the three types of real-time signals under a unified time reference to establish a dynamic feature basis that reflects beam response lag. The time misalignment analysis module, based on the established dynamic characteristics, continuously analyzes the time misalignment relationship between the radar echo energy change signal and the communication power time sequence signal, extracts the time boundary of the energy overlap interval, and obtains the instantaneous time window characterizing the main lobe interference trend. The beam advance adjustment module, combined with the obtained instantaneous time window, makes a slight advance adjustment to the update time sequence of the antenna array beam pointing, shifts the time range of the energy overlap interval in advance at the transmission control level, and generates the energy time distribution result of dynamic avoidance. The sampling synchronization adjustment module, based on the generated energy time distribution results of dynamic avoidance, performs synchronization delay adjustment on the triggering time sequence of the radar echo sampling process, realigns the sampling triggering time sequence with the beam pointing update time sequence on the time axis, and restores the master-slave correspondence of energy distribution. The power segmentation allocation module adaptively segments and allocates the communication signal power timing according to the restored master-slave correspondence, dynamically limiting the power distribution range within each radar scanning cycle, thus forming a coordinated balance between radar detection signals and communication transmission signals in terms of time and energy.

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