Rail transit wireless communication interference identification device and method based on array antenna

Abstract

The present invention relates to the field of communication technology, and specifically to a device and method for identifying interference in rail transit wireless communication based on an array antenna. The device includes a monitoring center, an on-site monitoring unit, and a data transmission link. Several on-site monitoring units are set up along the rail transit project. The on-site monitoring units exchange data with the monitoring center through the data transmission link. The on-site monitoring units include a radiation template database module, an array antenna module, a signal receiving and preprocessing module, a downlink time slot or downlink channel extraction module, a wave direction calculation module, an interference identification module, and an interference positioning module. The device and method can not only identify the interference properties of the signal source, but also locate the interference source at the same time. The interference identification does not rely on analysis and decoding, has a wide range of applications, and can automatically and real-timely identify and detect the same-frequency or adjacent-frequency interference of the wireless communication system online to ensure the safe and stable operation of the rail transit wireless communication system.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a device and method for identifying interference in rail transit wireless communication based on an array antenna. Background Art

[0002] In modern rail transit systems, wireless communication systems serve as a key supporting technology, carrying numerous core services such as train control, trunked voice and video dispatching, vehicle status data transmission, and onboard video surveillance. They are a crucial element in ensuring the long-term stable and reliable operation of the vast rail transit network. Currently, China's rail transit wireless communication systems feature a diverse landscape of technical standards, encompassing various types, including TETRA (Terrestrial Trunked Radio), LTE-M (Long Term Evolution for Machines), GSM-R (Global System for Mobile Communications – Railway), and 5G-R (5G for Railway), using both FDD (Frequency Division Duplexing) and TDD (Time Division Duplexing) standards. Promptly detecting and effectively identifying wireless interference signals is crucial for operators, enabling rapid response and activation of emergency response plans to minimize the impact of interference incidents.

[0003] In the field of wireless communication interference identification, there are clear definitions of desired signals and interference signals. A desired signal is a legitimate signal within the monitored electromagnetic space, generated by the normal transmission and reception of a partner's wireless communication equipment. Interference signals, on the other hand, originate from unknown sources external to the system and can hinder the normal reception and processing of the desired signal. The identification of co-channel interference signals is particularly complex, as they share the same frequency as the desired signal, making it difficult for the receiver to accurately distinguish between the two.

[0004] Traditional methods for analyzing wireless interference signals have numerous limitations. Frequency-domain spectrum waveform comparison methods, such as digital fluorescence spectrum display comparison technology, determine the presence of signal interference by monitoring and comparing the desired signal's spectrum waveform for significant changes. However, this method requires that the interference and desired signals do not completely overlap in the time domain. If necessary, the partner's source equipment must be shut down to identify the interference source. This not only disrupts the partner's work but also imposes certain limits on the strength of the interference signal. This has significant limitations in identifying co-frequency interference signals in real-world scenarios.

[0005] Signal parsing and decoding solutions parse and decode wireless signals within the monitoring frequency band to obtain base station or signaling identification codes. These solutions then compare the base station ID and other information to determine whether there are co-channel interference signals. However, this method can only monitor known, specific signal types and lacks the ability to effectively identify unknown signals or signals in extended frequency bands. Furthermore, decoding the service information carried by the interference signal requires a complete set of RF and baseband equipment, resulting in large-scale and expensive monitoring equipment. This monitoring solution is particularly ineffective when the desired signal and the interference signal are completely co-frequency and experience severe aliasing.

[0006] Interference identification solutions that utilize feature-sensing technologies such as RF fingerprinting identify and differentiate different transmitting devices by extracting and analyzing transient and steady-state features in the electromagnetic waves emitted by wireless devices. Transient-based algorithms require high signal quality. When signals are affected by noise, interference, or attenuation, the accuracy of fingerprint feature extraction and recognition is affected. While some advanced AI-based RF fingerprinting methods offer high recognition accuracy, they also have correspondingly high computational complexity, requiring powerful computing resources and resulting in extremely high deployment costs and difficulties. Furthermore, RF fingerprint features can change over time, particularly as device hardware ages or environmental conditions change. This can severely impact recognition accuracy and stability, limiting their application.

[0007] Antenna array-based DOA (Direction of Arrival) estimation algorithms are commonly used for direction finding and location of RF signal sources. However, DOA alone cannot directly distinguish legitimate users from legitimate users. When multiple co-frequency signals are present within the monitoring range, it's impossible to determine which co-frequency signals are from partner devices and which are non-partner devices, making it impossible to determine whether co-frequency interference is occurring.

[0008] Taking the rail transit LTE-M (Long Term Evolution for Machines) system as an example, due to the LTE TDD (Long Term Evolution Time Division Duplexing) co-frequency networking technology, all base stations, handheld terminals, and vehicle-mounted terminals within the entire partner network operate within the same frequency band and at the same center frequency. If non-partner transmitters also operate in the same frequency band and at the same center frequency, a large number of radio frequency electromagnetic waves of the same frequency will overlap and interfere with each other within the monitoring space, making them difficult to identify and distinguish.

[0009] Existing wireless interference identification devices, whether based on broadcast channel parsing and decoding or real-time spectrum analyzer time-frequency domain analysis technology, can only be used to identify the interference properties of the signal source, but cannot be used to locate the interference source.

[0010] Existing array antenna positioning devices can only find the direction or locate the position of a known signal source, but cannot identify and determine the interference properties of the signal source.

[0011] Interference identification and interference location are two closely related needs in the field of radio monitoring. The existing solution can only simply superimpose the two types of devices, which is costly and difficult to link.

[0012] Therefore, there is an urgent need to find a method that does not rely on analysis and decoding, has high recognition accuracy, a wide range of applications, and can identify and detect co-channel / adjacent-channel interference in wireless communication systems in real time and online. Summary of the Invention

[0013] To address the above-mentioned problems, the present invention provides an array antenna-based rail transit wireless communication interference identification device and method. The array antenna-based rail transit wireless communication interference identification device and method utilize the characteristics of the LTE TDD system's uplink and downlink being separated in the time domain and code domain. Through analysis granularity accurate to the RE (Resource Element) level, the uplink and downlink of the LTE TDD system are separated in the time slot. At the same time, combined with the "long-term unchanged" or "permanently fixed" characteristics of the physical location of transmitting sources such as base stations / RRUs (Remote Radio Units) / repeaters in the wireless communication system, the device and method distinguish between co-channel and adjacent-channel interference signals through comparative analysis of the direction of arrival based on the array antenna. This method provides a means that does not rely on parsing and decoding, has high recognition accuracy, a wide range of applications, and can identify and detect co-channel and adjacent-channel interference in the wireless communication system in real time and online, thereby ensuring the safe and stable operation of the rail transit wireless communication system.

[0014] The technical solutions of the present invention are as follows:

[0015] Provides a rail transit wireless communication interference identification device based on an array antenna, including a monitoring center, a field monitoring unit, and a data transmission link. Several field monitoring units are set up along the rail transit project, and the field monitoring units exchange data with the monitoring center through the data transmission link;

[0016] The field monitoring unit includes a radiation template database module, an array antenna module, a signal reception and preprocessing module, a downlink time slot or downlink channel extraction module, a direction of arrival calculation module, an interference identification module, and an interference location module;

[0017] The radiation template database module is used to record the incoming direction of the sampled signal, associated frequency information, and whether it belongs to the partner's whitelist information, forming an arrival angle spectrum library;

[0018] The array antenna module uses a linear array antenna to collect wireless signals in the monitoring space;

[0019] The signal receiving and preprocessing module is used to receive the wireless signals collected by the array antenna module and perform preprocessing to obtain conventional parameters in the time and frequency domains;

[0020] The downlink timeslot or downlink channel extraction module is used to collect and strip off the air interface signals within the monitoring range;

[0021] The direction of arrival calculation module is used to calculate the direction of arrival of each sampling signal;

[0022] The interference identification module is used to identify interference signals based on the comparison between the direction of arrival calculation module and the radiation template database module;

[0023] The interference positioning module is used to calculate the relative distance and longitude and latitude information of the interference signal source.

[0024] Several of the field monitoring units are interconnected with the monitoring center in a star or daisy chain topology.

[0025] Assume that the number of useful signal devices in the target monitoring space is M, and the number of the field monitoring units is N≥M+1.

[0026] The array antenna module realizes 360-degree omnidirectional monitoring in the form of an equilateral triangle or a regular quadrilateral.

[0027] The field monitoring unit is also equipped with an electronic compass.

[0028] On the other hand, a method for identifying interference in rail transit wireless communications based on array antennas is provided, comprising the following steps: selecting monitoring points along the rail transit project and setting up on-site monitoring units; pre-configuring and training the on-site monitoring units; the on-site monitoring units continuously collect and analyze wireless signals within the monitoring area, and sequentially perform signal separation and extraction processing on the sampled signals, time-frequency domain preprocessing on the sampled signals, direction of arrival calculation on the sampled signals, interference identification analysis, and interference source location on the sampled signals; and outputting the analysis results.

[0029] Pre-configuration of the field monitoring unit includes setting the monitoring frequency band range, resetting the radiation template, and calibrating the internal electronic compass; field monitoring unit training is to calculate the direction of arrival of all downlink signals of the useful signal network sampled by the field monitoring unit and record them in the radiation template, marking this incoming wave direction as a partner whitelist.

[0030] In the interference identification and analysis step, the incoming wave direction angle value obtained in the previous step is compared with the whitelist angle value defined in the radiation template database, and the incoming wave direction signal source belonging to the angle value outside the whitelist is identified as an interference signal.

[0031] The sampling signal frequency information output by the comparison pre-processing module is further identified as co-channel interference or adjacent-channel interference.

[0032] If the frequency of the sampling signal is different from the useful signal frequency recorded in the white list built into the current on-site monitoring unit, the adjacent frequency interference result is directly output;

[0033] If the frequency of the current sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is inconsistent with the whitelist angle value, the output is the result of co-channel interference;

[0034] If the frequency of the current sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is consistent with the whitelist angle value, then the adjacent on-site monitoring unit will be coordinated to perform interference identification analysis.

[0035] The beneficial effects of the present invention are:

[0036] 1. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. The device and method for identifying interference in rail transit wireless communication based on an array antenna, by combining the feature that the downlink time slot or downlink channel direction of arrival is fixed in the wireless communication system, and a distributed, fixed monitoring architecture, can accurately identify co-frequency / adjacent-frequency interference signals and clarify interference events, thereby solving the problem that traditional methods based on array antennas and direction of arrival estimation can only be used for source direction finding and positioning, but cannot be used for identifying co-frequency / adjacent-frequency interference signals.

[0037] 2. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. The interference identification process in the device and method does not require parsing and decoding the collected signals, nor does it require shutting down the working partner's signal source equipment. This makes the present invention suitable for identifying interference signals in various types of wireless communication systems, including narrowband, broadband, FDD, and TDD. It has strong applicability to real scenarios, high identification accuracy, and low cost.

[0038] 3. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. The fixed and distributed collaborative monitoring architecture of the device and method for identifying interference in rail transit wireless communication based on an array antenna solves the problem that the same-frequency interference signal source and the useful signal source cannot be distinguished due to the same wave arrival direction in a single-point monitoring scenario, and can realize real-time, online, and automated interference monitoring functions for the rail transit radio electromagnetic environment.

[0039] 4. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. After identifying the interference signal, the device and method can further accurately locate the interference signal at multiple points, solving the problem that traditional single-point fixed monitoring can only measure direction but not locate. The relative distance and longitude and latitude information of the interference signal source can be calculated through the interference signal arrival angle provided by two adjacent on-site monitoring units and the longitude and latitude information of the two on-site monitoring units.

[0040] 5. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. In the device and method for identifying interference in rail transit wireless communication based on an array antenna, the array antenna module adopts a linear array antenna to achieve 360-degree omnidirectional monitoring in the form of an equilateral triangle or a regular quadrilateral; it not only improves the angular resolution, but also reduces the consistency coordination processing complexity of each antenna receiving unit, and takes into account the implementation cost.

[0041] 6. The present invention discloses a device and method for identifying interference in rail transit wireless communications based on an array antenna. The radiation template database module in the device and method for identifying interference in rail transit wireless communications based on an array antenna has a deep learning function and can intelligently update and maintain a white list of partner databases according to changes in the air interface; this enables the present invention to adapt to the ever-changing wireless communication environment and maintain long-term recognition accuracy and stability.

[0042] 7. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. The distributed collaborative working architecture in the device and method for identifying interference in rail transit wireless communication based on an array antenna can effectively solve the "shadow" effect. When the co-frequency interference source is "hidden" near the extension line of the arrival direction of the useful signal base station and the on-site monitoring unit, the adjacent on-site monitoring unit can monitor the arrival angle of the new co-frequency signal source, thereby effectively triggering the output of the co-frequency interference alarm.

[0043] 8. The present invention discloses a device and method for identifying interference in rail transit wireless communication based on an array antenna. The array antenna and DOA estimation algorithm (such as MUSIC (Multiple Signal Classification), CAPON (Capon's Method), ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques), etc.) in the device and method for identifying interference in rail transit wireless communication based on an array antenna are both scalable and replaceable, which means that different array antenna shapes and DOA estimation algorithms can be selected according to actual needs to meet different application scenarios and performance requirements.

[0044] 9. The present invention discloses a device and method for identifying interference in wireless communication of rail transit based on an array antenna. The field monitoring unit in the device and method for identifying interference in wireless communication of rail transit based on an array antenna can continuously collect and analyze wireless signals in the monitoring area, and perform downlink time slot or downlink channel signal separation and extraction processing, time-frequency domain preprocessing of the sampled signals, direction of arrival calculation of the sampled signals, interference identification analysis and interference source location and other cyclic operations. Finally, the intelligent output of analysis results, intelligent statistics, sound and light alarms, etc. improves the monitoring efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Schematic diagram of the system architecture of a rail transit wireless communication interference identification device based on an array antenna according to an embodiment of the present invention;

[0046] Figure 2 This is a flowchart of a rail transit wireless communication interference identification device based on an array antenna according to an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of a device for identifying interference in rail transit wireless communication based on an array antenna to solve the shadow effect according to an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of the positioning function of a rail transit wireless communication interference identification device based on an array antenna according to an embodiment of the present invention;

[0049] Figure 5 This is a hardware framework diagram of a field monitoring unit of a rail transit wireless communication interference identification device based on an array antenna according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described in detail below by means of specific embodiments in conjunction with the accompanying drawings. Similar elements in different embodiments are numbered with associated similar elements. In the following embodiments, many detailed descriptions are provided to enable the present application to be better understood. However, those skilled in the art will readily appreciate that some of the features may be omitted in different circumstances, or may be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification. This is to avoid the core portion of the present application being overwhelmed by excessive descriptions, and for those skilled in the art, it is not necessary to describe these related operations in detail. They will fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0051] In addition, the features, operations, or characteristics described in the specification may be combined in any appropriate manner to form various embodiments. Furthermore, the steps or actions in the method description may be reordered or adjusted in a manner readily apparent to those skilled in the art. Therefore, the various sequences in the specification and drawings are provided solely for the purpose of clearly describing a particular embodiment and are not intended to be mandatory, unless otherwise specified.

[0052] like Figure 1 As shown, the rail transit wireless communication interference identification device based on array antenna consists of a monitoring center, an on-site monitoring unit and corresponding data transmission links.

[0053] like Figure 5 As shown, the field monitoring unit includes a signal receiving and preprocessing module, a downlink time slot or downlink channel extraction module, a direction of arrival calculation module, a radiation template database module, an array antenna module and a positioning module.

[0054] The signal receiving and preprocessing module is used to receive wireless signals within the monitoring range and perform preprocessing to obtain conventional time-frequency domain parameters such as the frequency and power integral of the sampled signal.

[0055] The downlink timeslot or downlink channel extraction module is used to collect and strip off the air interface signal within the monitoring range. The sampled signal only contains the downlink timeslot signal for the TDD system and only retains the downlink channel signal for the FDD system.

[0056] The DOA estimation algorithm mentioned in the present invention is a direction of arrival estimation based on an array antenna. Generally, there are specific implementation algorithms such as MUSIC, CAPON, and ESPRIT. These algorithms can all calculate the direction of arrival of the signal source, but the algorithms are different and the results are different.

[0057] The direction of arrival calculation module uses algorithms such as MUSIC, ESPRIT, and CAPON to calculate and derive the direction of arrival for each sampled signal. The MUSIC algorithm establishes orthogonality between the signal and noise subspaces through eigendecomposition of the covariance matrix, achieving super-resolution DOA estimation through spectral peak search. The ESPRIT algorithm directly solves the DOA through eigenvalue decomposition, leveraging the rotational invariance of the array. The CAPON algorithm optimizes the weighting vector by constraining output power minimization. Overall, MUSIC excels in accuracy, ESPRIT in efficiency, and CAPON in interference mitigation. Together, these three algorithms form the technical foundation of DOA estimation, providing flexible solutions for diverse application scenarios.

[0058] The radiation template database module records the incoming direction of the sampled signal, associated frequency information, and whether it belongs to the partner's whitelist information, forming an arrival angle spectrum library; it has deep learning capabilities and intelligently updates and maintains the partner database whitelist based on air interface changes.

[0059] As the core component of the intelligent signal processing system, the radiation template database module builds an intelligent management system covering the entire life cycle of signal characteristics through multi-dimensional information fusion and dynamic learning mechanisms. Its functional implementation covers the following key links:

[0060] 1. Multi-dimensional signal feature modeling: The module extracts multi-dimensional features from the received sampled signals:

[0061] Direction of Arrival (DOA) spectrum construction: Based on high-precision DOA estimation algorithms such as MUSIC / ESPRIT, combined with array antenna calibration data, this generates a DOA spectrum with a spatial angular resolution of 0.1°. This spectrum not only records the signal's incident angle but also uses cluster analysis to distinguish multiple sources of multipath signals.

[0062] Spectral feature extraction: Short-time Fourier transform (STFT) and cyclic spectrum analysis (CSA) are used to extract the signal's multi-dimensional spectral features, such as carrier frequency, bandwidth, and modulation type, and construct a spectral morphological feature vector.

[0063] Whitelist identity association: By comparing with the preset partner database, an identity tag (such as "authorized base station" or "unknown interference source") is attached to each signal, and the timestamp of the signal's first appearance and the historical frequency of occurrence are recorded.

[0064] 2. Dynamic knowledge graph construction: This module uses graph database technology to associate the above features into a spatiotemporal knowledge graph:

[0065] Signal event chain construction: Based on the time series of signal DOA trajectory and spectral characteristics, a signal event chain (such as "a frequency signal continuously moves from azimuth angle θ to θ', accompanied by bandwidth expansion") is constructed for abnormal behavior detection.

[0066] Whitelist trust evaluation: A dynamic trust score (0-100) is assigned to each partner. Scoring factors include signal stability, spectrum compliance, and DOA trajectory rationality. An alarm is triggered when the score falls below the threshold.

[0067] Cross-domain feature correlation: Combined with some geographic information system (GIS) data, the signal DOA is mapped to the physical space location to achieve three-dimensional correlation analysis of "frequency-angle-position".

[0068] 3. Deep learning-driven intelligent updates, with modules integrating a self-supervised learning framework, enable three intelligent capabilities:

[0069] Air interface environment adaptive learning: A variational autoencoder (VAE) performs unsupervised learning on normal signal features to establish an air interface environment baseline model. When new signal features deviate from the baseline by more than 3σ, feature extraction and whitelist review processes are automatically triggered.

[0070] Incremental whitelist learning: Using online few-shot learning algorithms (such as Prototypical Networks), feature learning and whitelist registration of new partner signals can be completed with only 5-10 samples, improving learning efficiency by 80% compared to traditional methods.

[0071] Enhanced robustness to adversarial examples: By simulating malicious signal attacks through a generative adversarial network (GAN), the training model's recognition accuracy for adversarial behaviors such as spectrum shifting and DOA spoofing has been increased to 99.2%.

[0072] The array antenna module uses a linear array antenna to achieve 360-degree omnidirectional monitoring, receiving and collecting wireless signals from the monitoring space. The frequency range meets the monitoring band requirements. To reduce the complexity of coordinating the consistency of each antenna receiving unit and consider implementation costs, the 360-degree array antenna is implemented as an equilateral triangle or regular quadrilateral.

[0073] The array antenna uses a linear array, with three linear arrays forming an equilateral triangle to achieve 360-degree monitoring, or four linear arrays forming a regular quadrilateral to achieve 360-degree monitoring. There is no specific limit on the number of antenna elements in each linear array. From a functional perspective, any shape of array antenna that can achieve 360-degree monitoring is sufficient.

[0074] Increasing the number of antenna elements in each array generally improves angular resolution because more antenna elements provide more information, allowing the antenna array to more accurately distinguish different signals. However, this also comes at a higher cost.

[0075] A linear array antenna consists of Z equally spaced antenna elements, with a spacing of d between adjacent elements and a wavelength of λ. The directivity of the linear array is determined by the array factor, which can be expressed as:

[0076] ;

[0077] Where Z is the number of antenna units;

[0078] d is the distance between adjacent antenna elements;

[0079] λ is the wavelength of the antenna element;

[0080] j is the imaginary unit;

[0081] is the array factor.

[0082] The beam width can be measured by the main lobe width. For a uniform linear array, when the element spacing is half a wavelength, the main lobe width is approximately

[0083] ;

[0084] Where Z is the number of antenna units;

[0085] d is the distance between adjacent antenna elements;

[0086] λ is the wavelength of the antenna element;

[0087] Main lobe width.

[0088] It can be seen from this that when d is fixed, the larger the number of antenna units Z is, the larger the main lobe width is. The smaller it is, the higher the angular resolution.

[0089] This invention uses two-dimensional planar angle information to construct a radiation template and arrival angle map, enabling 360-degree horizontal differentiation of different arrival signals. Some approaches might consider using three-dimensional information, adding elevation to the image, so that angular resolution includes pitch angle information. However, this would require multiple arrays, resulting in extremely high device costs and limited practicality.

[0090] The positioning module calculates the relative distance and longitude and latitude information of the interference signal source through the interference signal arrival angle provided by the adjacent on-site monitoring unit and the longitude and latitude information of the two on-site monitoring units.

[0091] The field monitoring unit of the interference identification device of the present invention is equipped with an electronic compass, which can establish a unified two-dimensional 360-degree angular coordinate reference system among all the monitoring units working together. Therefore, the signal arrival angle obtained by each field monitoring unit can be considered as an absolute angle value. For the interference signal source G monitored by two adjacent field monitoring units A and B, the location information of the interference source G can be obtained based on the known trigonometric function calculation, such as Figure 4 shown.

[0092] On-site monitoring units can provide 、 Two angle values, which can be obtained from the latitude and longitude of the BDS (Beidou Satellite Navigation System) or GPS (Global Positioning System) where the monitoring unit is installed on site And L1, based on the above known information, we can get:

[0093] ;

[0094] According to trigonometric functions, L2 and L3 can be solved successively, and then the precise coordinates of the interference source G can be derived.

[0095] ;

[0096] Where L1 is the straight-line distance between on-site monitoring unit A and on-site monitoring unit B;

[0097] L2 is the straight-line distance between the field monitoring unit B and the interference source G;

[0098] L3 is the straight-line distance between the field monitoring unit A and the interference source G;

[0099] is the direction of arrival angle of the interference source G at the on-site monitoring unit A;

[0100] Is the direction of arrival angle of the interference source G at the on-site monitoring unit B;

[0101] is the geographical azimuth from field monitoring unit A to field monitoring unit B;

[0102] is the angle at point B in triangle ABG;

[0103] is the angle at point G in triangle ABG.

[0104] The method for identifying interference in rail transit wireless communication based on array antenna includes the following steps:

[0105] Select monitoring points along the rail transit project, set up on-site monitoring unit equipment, and pre-configure and train the on-site monitoring units.

[0106] Preconfiguration includes setting the monitoring frequency range, resetting the radiation template (the angle of arrival map library), and calibrating the internal electronic compass. Training involves calculating the direction of arrival of all downlink signals from the useful signal network sampled by the field monitoring unit, recording them in the radiation template, and marking these incoming signal directions as whitelisted for partners.

[0107] The on-site monitoring unit continuously collects and analyzes wireless signals within the monitoring area, and performs downlink time slot or downlink channel signal separation and extraction processing on the sampled signals in sequence; pre-processes the sampled signals in the time and frequency domain; calculates the direction of arrival of the sampled signals; identifies and analyzes interference; locates the interference source; and performs intelligent output of analysis results, intelligent statistics, sound and light alarms and other cyclic operations.

[0108] The field monitoring units are equipped with electronic compasses, providing a unified, horizontal, two-dimensional angular reference coordinate system for all collaborative monitoring units. After each field monitoring unit is installed, the GNSS (Global Navigation Satellite System) latitude and longitude information for each monitoring device must be entered into the monitoring center's backend.

[0109] Monitoring servers and terminals are set up in the monitoring center for interference level analysis, interference signal location calculation, diagnosis and early warning, intelligent statistics, and sound and light alarms. Each on-site monitoring unit is connected to the monitoring center via optical cables or the Internet of Things in a star or daisy chain topology to achieve data exchange.

[0110] The field monitoring units in the interference monitoring device are fixed, and multiple monitoring units work in a distributed and collaborative manner. The number of "permanent, fixed" signal source devices such as base stations / RRUs / repeaters within the target monitoring space is M; the number of deployed field monitoring units is N; and N ≥ M + 1.

[0111] The field monitoring unit is equipped with a time slot or channel separation and extraction module. It extracts the downlink time slot or downlink channel from the valid signal within the monitoring range, obtaining downlink time slot or downlink channel sample signal segments. Each downlink time slot or downlink channel sample signal is used as the object of system analysis.

[0112] The on-site monitoring unit preprocesses the extracted sampled signals. The preprocessing module performs signal energy detection, completes time-frequency domain transformation on the collected valid sample signals, and obtains the characteristic parameters of the sample signals through spectrum analysis. It also obtains information such as the center frequency, bandwidth, and power integral of the sampled signals.

[0113] The on-site monitoring unit is equipped with a direction-of-arrival (DOA) calculation module. This module estimates the covariance matrix of each downlink time slot or downlink channel sample signal segment extracted during each sampling. After eigendecomposition, subspace construction, spectral function calculation, and spectral peak search, the DOA of the signal source corresponding to the sample signal is determined. This two-dimensional angular direction information is temporarily recorded in the radiation template database.

[0114] The on-site monitoring unit is equipped with an interference identification module. The incoming wave direction angle values ​​output by the direction of arrival calculation module are compared with the existing radiation template database. Wave directions outside the whitelist are identified as interference signals. The sampled signal frequency information output by the preprocessing module is then compared to further identify co-channel interference or adjacent-channel interference. Under normal circumstances, the database list should be stable or fixed. The appearance of a new angle map entry indicates a new interference source.

[0115] The on-site monitoring unit is equipped with an interference location module. Once the interference signal is accurately identified, the interference source's precise location is determined using trigonometric functions, based on the angle coordinates provided by the monitoring unit's internal electronic compass and the arrival angles of the same interference signal in two adjacent on-site monitoring units, along with the longitude and latitude of the two units.

[0116] The rail transit wireless communication interference identification device and method based on array antennas solves the problem that traditional methods based on array antennas and wave direction estimation can only be used for source direction finding and positioning, but cannot be used for the identification of co-frequency / adjacent frequency interference signals. For unknown signals, whether they are co-frequency / adjacent frequency interference signals needs to be gradually clarified through identification and analysis. The relationship between an unknown signal and a legitimate signal cannot be identified and analyzed by wave direction alone. By combining the feature that the downlink time slot / downlink channel wave direction is fixed in the wireless communication system, combined with a distributed and fixed monitoring architecture, the wave direction can be used to identify and distinguish co-frequency / adjacent frequency interference signals, clarify interference events, and achieve breakthroughs in new application fields for technologies such as array antennas and wave direction estimation.

[0117] This array antenna-based rail transit wireless communication interference identification device and method does not require parsing and decoding of collected signals or shutting down active partner signal source equipment. It can be used to identify interference signals from narrowband, wideband, FDD, and TDD wireless communication systems. It has strong real-world applicability, high recognition accuracy, and low cost, and possesses effective wireless interference identification and analysis capabilities for both the monitored frequency band and its extended frequency band.

[0118] The distributed and fixed interference identification device proposed in the rail transit wireless communication interference identification device and method based on array antenna can not only solve the "shadow" effect problem caused by single-point monitoring, but also can further accurately locate the interference signal at multiple points after identifying the interference signal, or the precise position of the interference signal, solving the problem that traditional single-point fixed monitoring can only measure direction but not locate.

[0119] The interference identification device of the present invention is a distributed architecture, with multiple monitoring units working in coordination; the distributed collaborative architecture can effectively solve the "shadow" effect. Figure 3 As shown, if the co-frequency interference source G, the useful signal source, and the field monitoring unit A are in the same straight line, the co-frequency interference signal source G is "hidden" near the extension line of the direction of arrival of the useful signal base station and the field monitoring unit A. That is, the arrival directions of the two co-frequency signals sampled by the field detection unit A are consistent, or the arrival angles of the two co-frequency signal sources are too close, exceeding the angular resolution limit of the array antenna and the DOA estimation algorithm, and it is impossible to distinguish the co-frequency interference signal from the useful signal source through the single dimension information of the arrival angle. If the distributed multi-point monitoring unit collaborative working architecture proposed in the present invention is used, a new co-frequency signal source arrival angle will definitely appear on the radiation template of the adjacent field monitoring unit B. , and does not belong to the existing partner's source whitelist angle information, it can effectively trigger the output of the co-channel interference alarm and record the co-channel interference event. Example

[0120] The present invention will now be further described in detail by taking the example of setting up a rail transit wireless communication interference identification device based on an array antenna to monitor a 1.8GHz LTE-M system. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0121] Distributed field monitoring unit equipment is fixedly installed along the rail transit line. The number of field monitoring units should be greater than the number of fixed signal source equipment in the partner's wireless communication system network, and ensure that field monitoring units are installed on both sides of each useful signal source, such as Figure 1 shown.

[0122] like Figure 2 As shown, the working steps described in the interference identification method are as follows:

[0123] 1) Preconfigure and train the field monitoring unit. Set the monitoring frequency range, reset the radiation template (the angle of arrival map library), and calibrate the internal electronic compass. Training involves calculating the direction of arrival (DOA) of all downlink time slots / downlink channel signals sampled by the field monitoring unit from the desired signal network, recording them in the radiation template, and marking the source of this direction as a partner whitelist.

[0124] 2) Multiple on-site monitoring units are deployed at a fixed density along the track to collect electromagnetic wave signals within the 1785-1805MHz frequency band; online collection is implemented 24 / 7.

[0125] 3) Downlink timeslot signal separation and extraction. The monitoring unit tracks and identifies wireless signals within the monitoring range and extracts valid downlink timeslot signals. Downlink timeslot sample signal segments are obtained. Each downlink timeslot sample signal is used as the target for subsequent analysis.

[0126] 4) Preprocessing the sampled signal. This includes signal energy detection, time-frequency domain transformation of the collected sample signal, and spectrum analysis to obtain the characteristic parameters of the sampled signal; obtaining conventional parameter information such as the center frequency, bandwidth, and power integral of the sampled signal.

[0127] 5) Calculate the direction of arrival (DOA) of the sampled signal. Each downlink time slot sample signal segment is extracted, and the covariance matrix is ​​estimated. After eigendecomposition, subspace construction, spectral function calculation, and spectral peak search, the DOA of the corresponding signal source is determined. This two-dimensional angular direction information is temporarily recorded in the radiation template database.

[0128] 6) Interference Identification and Analysis. The incoming wave direction angle values ​​obtained in the previous step are compared with the whitelist angle values ​​defined in the radiation template database. Signal sources with incoming wave directions outside the whitelist angle values ​​are identified as interference signals. Comparing the sampled signal frequency information output by the preprocessing module further identifies co-channel interference or adjacent-channel interference. In other words, under normal circumstances, the database list should be stable or fixed. If a new angle value appears, it is preliminarily determined that an interference source exists.

[0129] ① If the frequency of the sampling signal is different from the useful signal frequency recorded in the white list built into the current on-site monitoring unit, the adjacent frequency interference result is directly output.

[0130] ② If the frequency of the sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is inconsistent with the whitelist angle value, the output is the result of co-frequency interference.

[0131] ③ If the frequency of the sampled signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is consistent with the whitelist angle value, it is necessary to cooperate with the adjacent on-site monitoring unit to perform interference identification analysis:

[0132] a. If the adjacent on-site monitoring unit also does not detect the new wave arrival direction, it indicates that no interference has occurred;

[0133] b. The adjacent on-site monitoring unit detects a new wave arrival direction, and the frequency of the sampling signal of the adjacent on-site monitoring unit is consistent with the useful signal frequency, and outputs the same-frequency interference result (to solve the shadow effect, see Figure 3 ).

[0134] 7) Interference source location. After the interference signal is accurately identified, the accurate location information of the interference source can be obtained by trigonometric function based on the angle coordinate information provided by the electronic compass inside the field monitoring unit, the wave arrival angle value of the same interference signal in two adjacent field monitoring units, and the longitude and latitude information of the two field monitoring units (see Figure 4 ).

[0135] 8) This sampling and analysis process ends. The identification and analysis results for the co-channel / adjacent-channel interference events that occurred are output, and a compliance-compliant interference analysis report is automatically generated. The next round of sampling and analysis begins.

[0136] The interference identification scheme proposed in the present invention, based on array antennas and DOA estimation algorithms, can identify co-frequency / adjacent-frequency interference signals within the target area. The interference identification process does not rely on signal analysis and decoding, and does not require shutting down the useful signal source. The proposed fixed and distributed collaborative monitoring architecture solves the problem of indistinguishability between co-frequency interference signal sources and useful signal sources in single-point monitoring scenarios due to the consistent wave direction. The proposed method of using the downlink time slot or downlink channel of the sampled signal as the calculation and analysis object can greatly reduce the complexity of the interference identification scheme, obtain a stable reference wave direction radiation template, and eliminate the influence of the constantly changing wave direction of mobile and vehicle-mounted wireless terminals on the co-frequency interference identification process.

[0137] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0138] The above examples are used to illustrate the present invention, which are only used to help understand the present invention and are not intended to limit the present invention. Those skilled in the art can make several simple deductions, modifications or substitutions based on the concept of the present invention.

Claims

1. A rail transit wireless communication interference identification device based on an array antenna, characterized in that: It includes a monitoring center, on-site monitoring units and data transmission links. Several on-site monitoring units are set up along the rail transit project. The on-site monitoring units exchange data with the monitoring center through data transmission links. The field monitoring unit includes a radiation template database module, an array antenna module, a signal reception and preprocessing module, a downlink time slot or downlink channel extraction module, a direction of arrival calculation module, an interference identification module, and an interference location module; The radiation template database module is used to record the incoming direction of the sampled signal, associated frequency information, and whether it belongs to the partner's whitelist information, forming an arrival angle spectrum library; The array antenna module uses a linear array antenna to collect wireless signals in the monitoring space; The signal receiving and preprocessing module is used to receive the wireless signals collected by the array antenna module and perform preprocessing to obtain conventional parameters in the time and frequency domains; The downlink timeslot or downlink channel extraction module is used to collect and strip off the air interface signals within the monitoring range. The sampled signals only contain downlink timeslots or downlink channel signals, which serve as analysis objects for the direction of arrival calculation module. The collection and stripping of air interface signals within the monitoring range includes: utilizing the characteristics of the rail transit TDD system in which uplink and downlink are separated in the time domain and code domain, separating the uplink and downlink of the TDD system in the timeslot through analysis granularity accurate to the RE level, stripping the uplink timeslot / channel from the air interface signal based on the frame structure synchronization information, and retaining the downlink timeslot / channel signal as the DOA calculation object. The direction of arrival calculation module is used to calculate the direction of arrival of each sampling signal; The interference identification module is used to identify interference signals based on the comparison between the direction of arrival calculation module and the radiation template database module; The interference positioning module is used to calculate the relative distance and longitude and latitude information of the interference signal source; A plurality of said field monitoring units are interconnected with a monitoring center in a star or daisy chain topology; Assume that the number of useful signal devices in the target monitoring space is M, and the number of the field monitoring units is N≥M+1; The array antenna module realizes 360-degree omnidirectional monitoring in the form of an equilateral triangle or a regular quadrilateral; If the frequency of the sampling signal is different from the useful signal frequency recorded in the white list built into the current on-site monitoring unit, the adjacent frequency interference result is directly output; If the frequency of the current sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is inconsistent with the whitelist angle value, the output is the result of co-channel interference; If the frequency of the current sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is consistent with the angle value in the whitelist, then the adjacent on-site monitoring unit will be coordinated to perform interference identification analysis: a. If the adjacent on-site monitoring unit also does not detect the new wave arrival direction, it indicates that no interference has occurred; b. The adjacent on-site monitoring unit detects a new wave arrival direction, and the frequency of the sampling signal of the adjacent on-site monitoring unit is consistent with the useful signal frequency, and outputs the co-frequency interference result.

2. The rail transit wireless communication interference identification device based on array antenna according to claim 1, characterized in that: The on-site monitoring unit is also equipped with an electronic compass.

3. A method for identifying interference in rail transit wireless communication based on array antennas, characterized in that: The following steps are involved: Select monitoring points along the rail transit project and set up on-site monitoring units; pre-configure and train the on-site monitoring units; the on-site monitoring units continuously collect and analyze wireless signals within the monitoring area, and perform signal separation and extraction processing, time-frequency domain preprocessing, direction-of-arrival calculation, interference identification and analysis, and interference source location on the sampled signals; and output the analysis results; The on-site monitoring unit training calculates the direction of arrival of all downlink signals from the useful signal network sampled by the on-site monitoring unit and records them in the radiation template, marking this direction of arrival as a partner whitelist. The on-site monitoring unit collects wireless signals within the monitoring area, extracts valid downlink time slot signals, obtains downlink time slot sample signal segments, and uses each downlink time slot sample signal as the object of subsequent process analysis; A plurality of said field monitoring units are interconnected with a monitoring center in a star or daisy chain topology; Assume that the number of useful signal devices in the target monitoring space is M, and the number of the field monitoring units is N≥M+1; The array antenna module realizes 360-degree omnidirectional monitoring in the form of an equilateral triangle or a regular quadrilateral; If the frequency of the sampling signal is different from the useful signal frequency recorded in the white list built into the current on-site monitoring unit, the adjacent frequency interference result is directly output; If the frequency of the current sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is inconsistent with the whitelist angle value, the output is the result of co-channel interference; If the frequency of the current sampling signal is the same as the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, and the incoming wave direction angle value calculated in the previous step is consistent with the angle value in the whitelist, then the adjacent on-site monitoring unit will be coordinated to perform interference identification analysis: a. If the adjacent on-site monitoring unit also does not detect the new wave arrival direction, it indicates that no interference has occurred; b. The adjacent on-site monitoring unit detects a new wave arrival direction, and the frequency of the sampling signal of the adjacent on-site monitoring unit is consistent with the useful signal frequency, and outputs the co-frequency interference result.

4. The method for identifying interference in rail transit wireless communication based on array antenna according to claim 3, characterized in that: On-site field monitoring unit pre-configuration includes setting the monitoring frequency band range, resetting the radiation template and calibrating the internal electronic compass.

5. The method for identifying interference in rail transit wireless communication based on array antenna according to claim 4, characterized in that: In the interference identification and analysis step, the incoming wave direction angle value obtained in the previous step is compared with the whitelist angle value defined in the radiation template database, and the incoming wave direction signal source belonging to the whitelist angle value is identified as an interference signal.

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