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

Abstract

The invention relates to the technical field of communication, in particular to a rail transit wireless communication interference identification device and method based on an array antenna, and the device comprises a monitoring center, a plurality of field monitoring units and a data transmission link. The field monitoring unit performs data interaction with the monitoring center through a data transmission link; the field monitoring unit comprises 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 direction of arrival calculation module, an interference identification module and an interference positioning module. According to the device and the method, the signal source interference attribute can be identified, the interference source can be positioned at the same time, interference identification does not depend on analysis and decoding, the application range is wide, the same-frequency or adjacent-frequency interference of the wireless communication system can be automatically identified and detected on line in real time, and safe and stable operation of the rail transit wireless communication system is ensured.

Description

Technical Field

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

[0002] In modern rail transit systems, the wireless communication system, as a key supporting technology, carries numerous core services such as train control, trunked voice and video dispatching, vehicle status data transmission, and on-vehicle video monitoring. It is one of the core elements ensuring the long-term stable and reliable operation of a large rail transit network. Currently, the domestic rail transit wireless communication system presents a diversified technical standard pattern, covering various types such as TETRA (Terrestrial Trunked Radio), LTE-M (Long Term Evolution for Machines), GSM-R (Global System for Mobile Communications – Railway), 5G-R (5G for Railway), etc., and involving two different duplexing modes: FDD (Frequency Division Duplexing) and TDD (Time Division Duplexing). Timely detection and effective identification of radio interference signals are crucial for the operation department, as it helps to quickly respond and initiate emergency plans, minimizing the impact of interference events.

[0003] In the field of radio communication interference identification, useful signals and interference signals have clear definitions. A useful signal is a signal that legally exists in the monitored electromagnetic space environment and is generated by the normal transmission and reception of a cooperating party's radio communication equipment; while an interference signal comes from an unknown signal source outside the system and will prevent the normal reception and processing of useful signals. Among them, the identification of co-channel interference signals is particularly complex, as their frequencies are the same as those of useful signals, making it difficult for the receiver to accurately distinguish between the two.

[0004] Traditional radio interference signal analysis methods have many limitations. The frequency-domain spectrum waveform comparison scheme determines whether there is signal interference by monitoring and comparing whether there are obvious changes in the spectrum waveform of the useful signal, such as the digital fluorescence spectrum display comparison technology. However, this scheme requires that the interference and the useful signal are not completely coincident in the time domain, and it is necessary to turn off the cooperating party's signal source equipment to confirm the interference source when necessary. This not only causes the interruption of the cooperating party's work but also has certain limitations on the intensity of the interference signal, and has great limitations in the identification and application of co-channel interference signals in real scenarios.

[0005] The signal analysis and decoding scheme analyzes and decodes the wireless signals within the monitoring frequency band to obtain the base station or signaling identification code, and then determines whether there is a co-frequency interference signal by comparing information such as the base station ID. However, this method can only monitor known and specific signal types, and lacks effective identification ability for unknown signals or extended frequency band signals. At the same time, complete radio frequency and baseband equipment is required to decode the service information carried by the interference signal, resulting in a large scale and high cost of the monitoring equipment's software and hardware. Especially when the useful signal and the interference signal are completely co-frequency and severely overlapped, this monitoring scheme will fail.

[0006] The interference identification scheme using feature perception technologies such as radio frequency fingerprint recognition identifies and distinguishes different transmitting devices by extracting and analyzing the transient and steady-state features in the electromagnetic waves emitted by wireless devices. The algorithms based on transients have high requirements for signal quality. When the signal is affected by noise, interference or attenuation, it will affect the extraction and recognition accuracy of fingerprint features. Although some advanced radio frequency fingerprint recognition methods based on artificial intelligence have high recognition accuracy, their computational complexity is also relatively high, requiring powerful computing resource support, with extremely high deployment costs and difficulties. In addition, radio frequency fingerprint features will change over time, especially in the case of equipment hardware aging or environmental condition changes, seriously affecting the accuracy and stability of recognition, and the application has limitations.

[0007] The DOA (Direction of Arrival) estimation algorithm based on array antennas is usually used for the direction finding and positioning of radio frequency signal sources, but the signal source cannot be directly distinguished as a legitimate user only by the direction of arrival. When there are multiple co-frequency signals within the monitoring target range, it is impossible to determine which co-frequency signal sources belong to cooperative devices and which belong to non-cooperative devices, and thus it is impossible to judge whether there is a co-frequency interference event.

[0008] Taking the rail transit LTE-M (Long Term Evolution for Machines) system as an example, due to the technical characteristics of its LTE TDD (Long Term Evolution Time Division Duplexing) co-frequency networking, all base stations, handheld terminals, and vehicle-mounted terminals within the entire cooperative network operate within exactly the same frequency band range and have the same center frequency point. If various non-cooperative emission sources also operate on this frequency band and frequency point at this time, there will be a large number of radio frequency electromagnetic waves of the same frequency overlapping and interfering with each other within the monitoring space, and it is difficult to be identified and distinguished.

[0009] For existing wireless interference identification devices, whether based on broadcast channel parsing and decoding or on real-time spectrum analyzer time-frequency domain analysis technology, they can only be used to discriminate the interference attributes of signal sources and cannot be used to locate interference sources.

[0010] For existing array antenna positioning devices, they can only perform direction finding or positioning on the positions of known signal sources and cannot identify and judge the interference attributes of signal sources.

[0011] Interference identification and interference positioning are two closely related requirements in the field of radio monitoring. Existing solutions can only simply stack two types of devices, which is costly and difficult to link.

[0012] Therefore, there is an urgent need to seek a means that does not rely on parsing and decoding, has high identification accuracy, wide application range, 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 solve the above problems, the present invention provides a rail transit wireless communication interference identification device and method based on an array antenna. This rail transit wireless communication interference identification device and method utilize the characteristics that the uplink and downlink of the LTE TDD system are separated in the time domain and code domain, and through an analysis granularity accurate to the RE (Resource Element) level, separate the uplink and downlink of the LTE TDD system in time slots. At the same time, combined with the "long-term unchanged" or "permanently fixed" characteristics of the physical positions of transmit sources such as base stations / RRUs (Remote Radio Units) / repeaters in the wireless communication system, distinguish co-channel / adjacent-channel interference signals through direction-of-arrival comparison analysis based on the array antenna, and provide a means that does not rely on parsing and decoding, has high identification accuracy, wide application range, and can identify and detect co-channel / adjacent-channel interference in wireless communication systems in real-time and online to ensure the safe and stable operation of the rail transit wireless communication system.

[0014] The technical solution of the present invention is as follows: Provide 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. A number of field monitoring units are set along the rail transit project line, and the field monitoring units interact data with the monitoring center through the data transmission link; The field monitoring unit includes 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 direction-of-arrival calculation module, an interference identification module, and an interference positioning module; The radiation template database module is used to record the direction of arrival of the sampled signal, associate frequency information, and whether it belongs to the whitelist information of the cooperation party, forming an angle-of-arrival atlas library; The array antenna module uses a linear array antenna to collect wireless signals in the monitoring space; The signal reception and preprocessing module is used to receive the wireless signals collected by the array antenna module and perform preprocessing to obtain the conventional time-frequency domain parameters; The downlink time slot or downlink channel extraction module is used to collect and strip the air interface signals within the monitoring range; The direction-of-arrival calculation module is used to calculate the direction of arrival of each sampled signal; The interference identification module is used to identify interference signals by comparing the direction-of-arrival calculation module with the radiation template database module; The interference location module is used to infer the relative distance and longitude and latitude information of the interference signal source.

[0015] Several of the on-site monitoring units are interconnected with the monitoring center in a star or daisy-chain topology.

[0016] Let the number of useful signal devices in the target monitoring space be M, and the number of the on-site monitoring units be N≥M + 1.

[0017] The array antenna module realizes 360-degree omnidirectional monitoring in the form of an equilateral triangle or a square.

[0018] The on-site monitoring unit is also equipped with an electronic compass.

[0019] On the other hand, a method for identifying radio communication interference in rail transit based on an array antenna is provided, including the following steps: selecting monitoring points along the rail transit project and setting on-site monitoring units; pre-configuring and training the on-site monitoring units; the on-site monitoring units continuously collect and analyze the wireless signals in the monitoring area, and perform 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 on the sampled signals in sequence; outputting the analysis results.

[0020] The pre-configuration of the on-site monitoring unit includes setting the monitoring frequency band range, resetting the radiation template, and calibrating the internal electronic compass; the training of the on-site monitoring unit is to calculate the direction of arrival of all downlink signals of the useful signal network sampled by the on-site monitoring unit and record them in the radiation template, marking this direction of arrival as the whitelist of the cooperation party.

[0021] In the interference identification analysis step, the direction-of-arrival angle value obtained in the previous step is compared with the whitelist angle value defined in the radiation template database, and the signal source with a direction of arrival outside the whitelist angle value is identified as an interference signal.

[0022] The frequency information of the sampled signal output by the comparison preprocessing module is further identified as co-channel interference or adjacent-channel interference.

[0023] If the frequency of the current sampled signal is different from the frequency of the useful signal recorded in the built-in whitelist of the current on-site monitoring unit, the result of adjacent-channel interference is directly output; If the frequency of the current sampled signal is the same as the frequency of the useful signal recorded in the built-in whitelist of the current on-site monitoring unit, and the angle value of the wave arrival direction calculated in the previous step is inconsistent with the whitelist angle value, the result of co-channel interference is output; If the frequency of the current sampled signal is the same as the frequency of the useful signal recorded in the built-in whitelist of the current on-site monitoring unit, and the angle value of the wave arrival direction calculated in the previous step is consistent with the whitelist angle value, the adjacent on-site monitoring units are coordinated for interference identification and analysis.

[0024] The beneficial effects of the present invention are as follows: 1. A rail transit wireless communication interference identification device and method based on an array antenna disclosed by the present invention. By combining the feature that the wave arrival direction of the downlink time slot or downlink channel of the wireless communication system is fixed, and the distributed and fixed monitoring architecture, the co-channel / adjacent-channel interference signals can be accurately identified, and interference events can be clarified, solving the problem that the traditional method based on array antenna and wave arrival direction estimation can only be used for signal source direction finding and positioning, but cannot be used for co-channel / adjacent-channel interference signal identification.

[0025] 2. A rail transit wireless communication interference identification device and method based on an array antenna disclosed by the present invention. In the interference identification process of the rail transit wireless communication interference identification device and method based on an array antenna, it is not necessary to analyze and decode the collected signals, nor to turn off the working cooperative signal source device, which makes the present invention applicable to the identification of interference signals in various types of wireless communication systems such as narrowband, broadband, FDD, and TDD, with strong applicability to real scenarios, high identification accuracy, and low cost.

[0026] 3. A rail transit wireless communication interference identification device and method based on an array antenna disclosed by the present invention. The fixed and distributed collaborative monitoring architecture of the rail transit wireless communication interference identification device and method based on an array antenna solves the problem that the co-channel interference signal source and the useful signal source cannot be distinguished due to the same wave arrival direction in the single-point monitoring scenario, and can realize the real-time, online, and automatic interference monitoring function of the rail transit wireless electromagnetic environment.

[0027] 4. A device and method for identifying radio communication interference in rail transit based on an array antenna. After identifying the interference signal, the device and method for identifying radio communication interference in rail transit based on an array antenna can further perform multi-point precise positioning on the interference signal, solving the problem that traditional single-point fixed monitoring can only measure direction but not position. Based on the arrival angles of the interference signals provided by two adjacent on-site monitoring units and the longitude and latitude information of the two on-site monitoring units, the relative distance and longitude and latitude information of the interference signal source can be calculated.

[0028] 5. A device and method for identifying radio communication interference in rail transit based on an array antenna. In the device and method for identifying radio communication interference in rail transit based on an array antenna, the array antenna module uses a linear array antenna to achieve 360-degree omnidirectional monitoring in the form of an equilateral triangle or a square. It not only improves the angle resolution but also reduces the complexity of the consistency coordination processing of each antenna receiving unit, and takes into account the implementation cost.

[0029] 6. A device and method for identifying radio communication interference in rail transit based on an array antenna. In the device and method for identifying radio communication interference in rail transit based on an array antenna, the radiation template database module has a deep learning function and can intelligently update and maintain the white list of the partner database according to the changes in the air interface. This enables the present invention to adapt to the constantly changing radio communication environment and maintain long-term identification accuracy and stability.

[0030] 7. A device and method for identifying radio communication interference in rail transit based on an array antenna. In the device and method for identifying radio communication interference in rail transit based on an array antenna, the distributed collaborative working architecture can well solve the "shadow" effect. When the co-frequency interference source is "hidden" near the extension line of the arrival direction between the useful signal base station and the on-site monitoring unit, the adjacent on-site monitoring units can monitor the arrival angle of the new co-frequency signal source, thus effectively triggering the output of the co-frequency interference warning.

[0031] 8. 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, both the array antenna and DOA estimation algorithms (such as MUSIC (Multiple Signal Classification), CAPON (Capon's Method), ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques), etc.) are scalable and replaceable, meaning that different array antenna shapes and DOA estimation algorithms can be selected according to actual needs to meet different application scenarios and performance requirements.

[0032] 9. 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 on-site monitoring unit can continuously collect and analyze wireless signals in the monitoring area, and perform cyclic operations such as separating and extracting downlink time slots or downlink channel signals from the sampled signals, preprocessing the sampled signals in the time-frequency domain, calculating the direction of arrival of the sampled signals, interference identification and analysis, and interference source localization. Finally, it intelligently outputs analysis results, intelligent statistics, sound and light alarms, etc., improving the monitoring efficiency and accuracy. Description of the Drawings

[0033] Figure 1 It is a schematic diagram of the system architecture of a device for identifying interference in rail transit wireless communication based on an array antenna according to an embodiment of the present invention; Figure 2 It is a flowchart of the operation of a device for identifying interference in rail transit wireless communication based on an array antenna according to an embodiment of the present invention; Figure 3 It is a schematic diagram of a device for identifying interference in rail transit wireless communication based on an array antenna according to an embodiment of the present invention to solve the shadow effect; Figure 4 It is a schematic diagram of the positioning function of a device for identifying interference in rail transit wireless communication based on an array antenna according to an embodiment of the present invention; Figure 5 It is a hardware framework structure diagram of the on-site monitoring unit of a device for identifying interference in rail transit wireless communication based on an array antenna according to an embodiment of the present invention. Detailed Embodiments

[0034] The present invention will be further described in detail below in conjunction with the specific embodiments and the accompanying drawings. Similar elements in different embodiments are denoted by related similar element numbers. In the following embodiments, many detailed descriptions are provided to enable a better understanding of the present application. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can 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 to avoid overwhelming the core part of the present application with excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and the general technical knowledge in the art.

[0035] In addition, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can also be reordered or adjusted in a manner obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for clearly describing a certain embodiment and do not mean that they are necessary sequences, unless it is stated otherwise that a certain sequence must be followed.

[0036] As Figure 1 shown, the rail transit wireless communication interference identification device based on an array antenna is composed of a monitoring center, a field monitoring unit, and a corresponding data transmission link.

[0037] As Figure 5 shown, the field monitoring unit includes a signal reception and preprocessing module, a downlink time slot or downlink channel extraction module, a direction of arrival calculation module, a radiation pattern database module, an array antenna module, and a positioning module.

[0038] The signal reception 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 integration of the sampled signals.

[0039] The downlink time slot or downlink channel extraction module is used to collect and strip the air interface signals within the monitoring range. The sampled signals only contain downlink time slot signals for TDD systems and only retain downlink channel signals for FDD systems.

[0040] The DOA estimation algorithm mentioned in the present invention is the 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 only the algorithms are different and the effects are different.

[0041] The direction-of-arrival (DOA) calculation module uses algorithms such as MUSIC, ESPRIT, and CAPON to calculate and obtain the direction of arrival of the sampled signal each time. The MUSIC algorithm constructs the orthogonality between the signal and noise subspaces through the eigen-decomposition of the covariance matrix, and realizes super-resolution DOA estimation through spectral peak search. The ESPRIT algorithm utilizes the rotational invariance property of the array and directly solves the DOA through eigen-value decomposition. The CAPON algorithm optimizes the weighting vector by minimizing the output power under constraints. Generally speaking, MUSIC is known for its accuracy, ESPRIT wins in terms of efficiency, and CAPON takes the core advantage in anti-interference ability. The three together constitute the technical foundation of DOA estimation and provide flexible solutions for different application scenarios.

[0042] The radiation pattern database module records the direction of arrival of the sampled signal, associates frequency information, and whether it belongs to the whitelist information of the cooperation party, forming a direction-of-arrival angle atlas library. It has deep learning capabilities and can intelligently update and maintain the whitelist of the cooperation party database according to the changes in the air interface.

[0043] As the core component of the intelligent signal processing system, the radiation pattern database module constructs an intelligent management system covering the entire life cycle of signal characteristics through multi-dimensional information fusion and dynamic learning mechanisms. The realization of its functions covers the following key links: 1. Multi-dimensional signal feature modeling. The module performs multi-dimensional feature extraction on the received sampled signal: DOA spectrogram construction: Based on high-precision DOA estimation algorithms such as MUSIC / ESPRIT, combined with array antenna calibration data, a direction-of-arrival angle spectrogram with a spatial angle resolution of 0.1° is generated. This spectrogram not only records the incident angle of the signal, but also distinguishes multi-source signals under multipath effects through clustering analysis.

[0044] Spectrum feature extraction: Using the short-time Fourier transform (STFT) and cyclic spectral analysis (CSA), multi-dimensional spectrum features such as the carrier frequency, bandwidth, and modulation type of the signal are extracted, and a spectrum morphological feature vector is constructed.

[0045] Whitelist identity association: By comparing with the preset cooperation party database, an identity label (such as "authorized base station", "unknown interference source") is attached to each signal, and the timestamp of the signal's first appearance and the historical appearance frequency are recorded.

[0046] 2. Dynamic knowledge graph construction. The module uses graph database technology to associate the above features into a spatio-temporal integrated knowledge graph: Signal event chain construction: Based on the time series of the signal's DOA trajectory and spectrum features, a signal event chain (such as "a signal with a certain frequency continuously moves from azimuth angle θ to θ' and is accompanied by bandwidth expansion") is constructed for abnormal behavior detection.

[0047] Whitelist Trustworthiness Assessment: Assign a dynamic trustworthiness score (0 - 100) to each partner. The scoring factors include signal appearance stability, spectrum compliance, DOA trajectory rationality, etc. An alarm is triggered when the score is below the threshold.

[0048] Cross - domain Feature Association: Combine some Geographic Information System (GIS) data, map the signal DOA to physical space positions, and achieve three - dimensional correlation analysis of "frequency - angle - position".

[0049] 3. Deep - learning - driven Intelligent Update. The module integrates a self - supervised learning framework to achieve three major intelligent capabilities: Radio Environment Adaptive Learning: Use a Variational Auto - Encoder (VAE) to perform unsupervised learning on normal signal features and establish a radio environment baseline model. When the new signal features deviate from the baseline by more than 3σ, the feature extraction and whitelist review processes are automatically triggered.

[0050] Whitelist Incremental Learning: Adopt an online few - shot learning algorithm (such as Prototypical Networks). It can complete the feature learning and whitelist registration of new partner signals with only 5 - 10 samples, and the learning efficiency is increased by 80% compared with traditional methods.

[0051] Enhanced Robustness to Adversarial Samples: Simulate malicious signal attacks through a Generative Adversarial Network (GAN), and the recognition accuracy of the model for adversarial behaviors such as spectrum shifting and DOA deception is increased to 99.2%.

[0052] The array antenna module uses a linear array antenna to achieve 360 - degree omnidirectional monitoring, receive and collect wireless signals in the monitoring space, and the frequency range meets the monitoring band requirements. Considering reducing the complexity of the consistency coordination processing of each antenna receiving unit and the implementation cost, the 360 - degree array antenna is implemented in the form of an equilateral triangle or a square.

[0053] The array antenna uses a linear array, and 360 - degree monitoring is achieved by forming an equilateral triangle with 3 groups of linear arrays or a square with 4 groups of linear arrays. And there is no clear limit on the number of antenna units in each group of linear arrays. In terms of function implementation, as long as the array antenna of any shape can achieve 360 - degree monitoring.

[0054] Increasing the number of antenna units in each group of array antennas usually improves the angular resolution because more antenna units can provide more information, enabling the antenna array to more accurately distinguish different signals. However, the cost is also higher.

[0055] The linear array antenna consists of Z equally - spaced antenna units, with the adjacent unit spacing being d and the wavelength being λ. The radiation pattern of the linear array is determined by the array factor, and the array factor can be expressed as: ;

[0056] Wherein, Z is the number of antenna elements; d is the spacing between adjacent antenna elements; λ is the wavelength of the antenna element; j is the imaginary unit; is the array factor.

[0057] 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 ;

[0058] Wherein, Z is the number of antenna elements; d is the spacing between adjacent antenna elements; λ is the wavelength of the antenna element; Main lobe width.

[0059] It can be seen from this that when d is fixed, the larger the number of antenna elements Z, the smaller the main lobe width and the higher the angular resolution.

[0060] The present invention mentions using two-dimensional plane angle information to form a radiation template and an angle-of-arrival map, and distinguishing different angle-of-arrival signals in the horizontal 360 degrees. Some ideas may mention three-dimensional information to increase the elevation, so that the angle resolution includes the pitch angle information, but this requires multiple planar arrays to implement, which will lead to extremely high cost and extremely low practicability of the device.

[0061] The positioning module calculates the relative distance and longitude and latitude information of the interference signal source based on the angle of arrival of the interference signal provided by adjacent on-site monitoring units and the longitude and latitude information of two on-site monitoring units.

[0062] The on-site monitoring unit of the interference identification device described in the present invention is built-in with an electronic compass, which can establish a unified two-dimensional 360-degree angle coordinate reference system among all cooperating monitoring units. Therefore, the angle of arrival of the signal obtained by each on-site monitoring unit can be considered as an absolute angle value. For the interference signal source G jointly monitored by two adjacent on-site monitoring units A and B, the position information of the interference source G can be calculated according to the known trigonometric functions, as Figure 4 shown.

[0063] The on-site monitoring unit can provide , Two angle values, and the longitude and latitude of the BDS (BeiDou Navigation Satellite System) or GPS (Global Positioning System) where the on-site monitoring unit is installed can obtain And L1, based on the above-known information, we can obtain: ;

[0064] According to trigonometric functions, L2 and L3 can be successively calculated, and then the precise coordinates of the interference source G can be deduced.

[0065] ;

[0066] In the formula, L1 is the straight-line distance between the on-site monitoring unit A and the on-site monitoring unit B; L2 is the straight-line distance between the on-site monitoring unit B and the interference source G; L3 is the straight-line distance between the on-site monitoring unit A and the interference source G; is the angle of arrival direction of the interference source G at the on-site monitoring unit A; is the angle of arrival direction of the interference source G at the on-site monitoring unit B; is the geographical azimuth angle from the on-site monitoring unit A to the on-site monitoring unit B; is the angle at point B in the triangle ABG; is the angle at point G in the triangle ABG.

[0067] The rail transit wireless communication interference recognition method based on an array antenna includes the following steps: Select monitoring points along the rail transit project, set up on-site monitoring unit equipment, and perform pre-configuration and training on the on-site monitoring unit.

[0068] The pre-configuration includes setting the monitoring frequency band range, resetting the radiation template (angle of arrival pattern library), and calibrating the internal electronic compass. The training is to calculate the angle of arrival of all downlink signals of the useful signal network sampled by the on-site monitoring unit and record them in the radiation template, and mark this incoming wave direction as the partner whitelist.

[0069] The on-site monitoring unit continuously collects and analyzes the wireless signals in the monitoring area, and successively performs downlink time slot or downlink channel signal separation and extraction processing on the sampled signals; time-frequency domain preprocessing of the sampled signals; angle of arrival calculation of the sampled signals; interference recognition analysis; interference source positioning; intelligent output of analysis results, intelligent statistics, sound and light alarms, and other cyclic operations.

[0070] An electronic compass is configured in the on-site monitoring unit, enabling each monitoring unit working in coordination to have a unified horizontal two-dimensional angular reference coordinate system. After each on-site monitoring unit is installed and fixed, the GNSS (Global Navigation Satellite System) longitude and latitude information of each monitoring device must be entered into the background of the monitoring center.

[0071] A monitoring server and terminals are set up in the monitoring center for interference degree analysis, interference signal position calculation, diagnosis and early warning, intelligent statistics, audible and visual alarms, etc. Each on-site monitoring unit is interconnected with the monitoring center in a star or daisy-chain topology through optical cables or the Internet of Things to achieve data interaction.

[0072] The on-site monitoring units in the interference monitoring device are set in a fixed manner, and multiple monitoring units work in a distributed and coordinated manner. The number of "permanent and fixed" signal source devices such as useful signal base stations / RRUs / repeaters in the target monitoring space is M; the number of on-site monitoring unit devices deployed is N; it is required that N≥M + 1; A time slot or channel separation and extraction module is configured in the on-site monitoring unit. The downlink time slot or downlink channel of the effective signals within the monitoring range is stripped and extracted to obtain a downlink time slot or downlink channel sample signal segment. Each downlink time slot or downlink channel sample signal obtained by each sampling is used as the object for system analysis.

[0073] The on-site monitoring unit preprocesses the extracted sampling signals. The preprocessing module performs signal energy detection, completes time-frequency domain transformation on the collected effective sample signals, and obtains the characteristic parameters of the sample signals after spectrum analysis; information such as the center frequency point, frequency bandwidth, and power integration of the sampling signals is obtained.

[0074] A direction-of-arrival calculation module is configured in the on-site monitoring unit. The covariance matrix of each downlink time slot or downlink channel sample signal segment extracted by each sampling is estimated, and after steps such as eigenvalue decomposition, subspace construction, spectral function calculation, and spectral peak search, the direction of arrival of the signal source corresponding to the sample signal is determined. And this two-dimensional angular direction information is temporarily recorded in the radiation template database.

[0075] An interference identification module is configured in the on-site monitoring unit. The angle value of the direction of arrival of the incoming wave output by the direction-of-arrival calculation module is compared in the existing radiation template database. The incoming wave direction belonging to outside the white list can be identified as an interference signal, and further identification as co-channel interference or adjacent-channel interference can be made by comparing the frequency information of the sampling signals output by the preprocessing module. Normally, the database list should be stable or unchanged. If new angle spectrum entries appear, they are new interference sources.

[0076] The on-site monitoring unit is configured with an interference location module. After the interference signal is accurately identified, based on the angle coordinate information provided by the internal electronic compass of the monitoring unit, and according to the angle of arrival values of the same interference signal in two adjacent on-site monitoring units and the longitude and latitude information of the two on-site monitoring units, the accurate location information of the interference source can be obtained through trigonometric functions.

[0077] The rail transit wireless communication interference identification device and method based on an array antenna solve the problem that the traditional method based on an array antenna and direction of arrival estimation can only be used for signal source direction finding and positioning and cannot be used for the identification of co-channel / adjacent-channel interference signals. For an unknown signal, whether it is a co-channel / adjacent-channel interference signal needs to be gradually clarified through identification and analysis. Only relying on the direction of arrival cannot identify and analyze the relationship between an unknown signal and a legitimate signal. By combining the characteristic that the direction of arrival of the downlink time slot / downlink channel in the wireless communication system is fixed, and combining a distributed and fixed monitoring architecture, the direction of arrival can be used to identify and distinguish co-channel / adjacent-channel interference signals, clarify interference events, and achieve a breakthrough in the application of new fields for technologies such as array antennas and direction of arrival estimation.

[0078] The interference identification process of the rail transit wireless communication interference identification device and method based on an array antenna does not require parsing and decoding of the collected signals, and does not require shutting down the cooperating signal source devices that are working. It can be used for the identification of interference signals in various types of wireless communication systems such as narrowband, broadband, FDD, and TDD. It has strong applicability in real scenarios, high identification accuracy, and low cost, and has effective wireless interference identification and analysis capabilities for the monitored frequency band and its extended frequency bands.

[0079] The distributed and fixed interference identification device proposed by the rail transit wireless communication interference identification device and method based on an array antenna can not only solve the "shadow" effect problem caused by single-point monitoring, but also further perform multi-point precise positioning on the interference signal after identifying the interference signal, or determine the accurate location of the interference signal, solving the problem that traditional single-point fixed monitoring can only perform direction finding and cannot perform positioning.

[0080] The interference identification device described in the present invention has a distributed architecture, and multiple monitoring units work together; the distributed cooperative working architecture can well solve the "shadow" effect. For example Figure 3As shown in the figure, when the co-channel interference source G, the useful signal source, and the on-site monitoring unit A are on the same straight line, the co-channel interference signal source G is "hidden" near the extension line of the direction of arrival of the useful signal base station and the on-site monitoring unit A. That is, the directions of arrival of the two co-channel signals sampled by the on-site detection unit A are the same, or the angles of arrival of the two co-channel signal sources are too close, exceeding the angle resolution limit of the array antenna and the DOA estimation algorithm, and it is impossible to distinguish the co-channel interference signal and the useful signal source through the single-dimensional information of the angle of arrival. If the collaborative working architecture of distributed multi-point monitoring units proposed by the present invention is adopted, a new angle of arrival of the co-channel signal source will surely appear on the radiation template of the adjacent on-site monitoring unit B at this time , and it does not belong to the angle information of the white list of the existing partner signal sources, then it can effectively trigger the output of co-channel interference alarms and record co-channel interference events. Embodiment

[0081] Taking the example of setting up a rail transit wireless communication interference recognition device based on an array antenna to monitor the 1.8 GHz LTE-M system, the present invention will be further described in detail. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0082] Install distributed on-site monitoring unit devices fixedly along the rail transit line. The number of on-site monitoring units should be greater than the number of fixed signal source devices in the partner wireless communication system network, and it is ensured that on-site monitoring units are set on both sides of each useful signal source, as Figure 1 shown.

[0083] As Figure 2 shown, the working steps described in the interference recognition method are as follows: 1) Pre-configure and train the on-site monitoring unit. Set the monitoring frequency band range, reset the radiation template (angle of arrival map library), and calibrate the internal electronic compass. The training is to calculate the direction of arrival of all downlink time slots / downlink channel signals of the useful signal network sampled by the on-site monitoring unit and record them in the radiation template, and mark the source of this direction of arrival as the partner white list.

[0084] 2) Fixedly deploy multiple on-site monitoring unit devices along the track at a certain density, and on-site collect electromagnetic wave signals in the frequency band range of 1785 - 1805 MHz; implement 7×24-hour online collection.

[0085] 3) Downlink time slot signal separation and extraction processing. The monitoring unit tracks and identifies the wireless signals within the monitored range, extracts the effective downlink time slot signals, and obtains the downlink time slot sample signal segments. Take the downlink time slot sample signals sampled each time as the object of analysis for the subsequent process.

[0086] 4) Preprocess the sampled signal. This includes signal energy detection, performing time-frequency domain transformation on the acquired sample signal, and obtaining the characteristic parameters of the sampled signal through spectral analysis; obtaining conventional parameter information such as the center frequency point, frequency bandwidth, and power integration of the sampled signal.

[0087] 5) Calculate the direction of arrival (DOA) of the sampled signal. For each extracted downlink time slot sample signal segment, estimate the covariance matrix, and after steps such as eigen-decomposition, subspace construction, spectral function calculation, and spectral peak search, determine the DOA of the signal source corresponding to the sample signal. And temporarily record this two-dimensional angle direction information in the radiation template database.

[0088] 6) Interference identification and analysis. Compare the angle value of the incoming wave direction obtained in the previous step with the whitelist angle values defined in the radiation template database. The incoming wave direction signal source outside the whitelist angle values can be identified as an interference signal, and by comparing the frequency information of the sampled signal output by the preprocessing module, it can be further identified as co-channel interference or adjacent-channel interference. That is, normally the database list should be stable or fixed. If new angle values appear, it is initially determined that there is an interference source.

[0089] ① If the frequency of the current sampled signal is different from the frequency of the useful signal recorded in the whitelist built into the current on-site monitoring unit, directly output the result of adjacent-channel interference.

[0090] ② If the frequency of the current sampled signal is the same as the frequency of the useful signal recorded in the whitelist built into the current on-site monitoring unit, and the angle value of the incoming wave direction calculated in the previous step is inconsistent with the whitelist angle value, output the result of co-channel interference.

[0091] ③ If the frequency of the current sampled signal is the same as the frequency of the useful signal recorded in the whitelist built into the current on-site monitoring unit, and the angle value of the incoming wave direction calculated in the previous step is consistent with the whitelist angle value, then it is necessary to cooperate with adjacent on-site monitoring units for interference identification and analysis: a. If no new direction of arrival is detected by the adjacent on-site monitoring unit either, it is prompted that there is no interference; b. If the adjacent on-site monitoring unit detects a new direction of arrival, and the frequency of the sampled signal of the adjacent on-site monitoring unit in this sampling is the same as the frequency of the useful signal, output the result of co-channel interference (to solve the shadow effect, see Figure 3 )

[0092] 7) Interference source localization. After the interference signal is accurately identified, based on the angle coordinate information provided by the internal electronic compass of the on-site monitoring unit, according to the DOA values of the same interference signal in two adjacent on-site monitoring units, and the longitude and latitude information of the two on-site monitoring units, the accurate position information of the interference source can be obtained through trigonometric functions (see Figure 4 )

[0093] 8) End the current sampling and analysis process. For the co-frequency / adjacent-frequency interference events occurring in this process, output the recognition and analysis results, and automatically generate a compliance interference analysis report. Then enter the next round of sampling and analysis process.

[0094] The interference recognition solution based on array antennas and DOA estimation algorithms proposed by the present invention can realize the recognition of co-frequency / adjacent-frequency interference signals in the target area. The interference recognition process does not depend on the parsing and decoding of signals and does not require the shutdown of useful signal sources; the proposed monitoring architecture with fixed and distributed collaborative work solves the problem that the co-frequency interference signal source and the useful signal source cannot be distinguished due to the same direction of arrival in the single-point monitoring scenario; the proposed method of using the downlink time slot or downlink channel of the sampling signal as the object of calculation and analysis can greatly reduce the complexity of the interference recognition solution, obtain a stable reference direction of arrival radiation template, and remove the influence of the continuously changing direction of arrival of mobile and vehicle-mounted wireless terminals on the co-frequency interference recognition process.

[0095] In the description of this specification, the descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection 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 a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0096] The above uses specific examples to elaborate on the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the technical field to which the present invention pertains, based on the idea of the present invention, several simple deductions, deformations, or substitutions can also be made.

Claims

1. A rail transit wireless communication interference identification device based on an array antenna, characterized in that: It includes a monitoring center, field monitoring units and data transmission links. Several field monitoring units are set up along the rail transit project. The field 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 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 radiation template database module is used to record the incoming direction of the sampled signal, the 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 time slot or downlink channel extraction module is used to collect and strip the air interface signals within the monitoring range; The wave direction calculation module is used to calculate the wave direction of each sampling signal; The interference identification module is used to identify interference signals by comparing the direction of arrival calculation module with 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.

2. The rail transit wireless communication interference identification device based on array antenna according to claim 1, characterized in that: A plurality of the field monitoring units are interconnected with the monitoring center in a star or daisy chain topology.

3. The rail transit wireless communication interference identification device based on array antenna according to claim 1, characterized in that: 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.

4. The rail transit wireless communication interference identification device based on array antenna according to claim 1, characterized in that: The array antenna module realizes 360-degree omnidirectional monitoring in the form of an equilateral triangle or a regular quadrilateral.

5. 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.

6. 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 in the monitoring area, and perform signal separation and extraction processing, time-frequency domain preprocessing, direction of arrival calculation, interference identification analysis and interference source location on the sampled signals in sequence; and output the analysis results.

7. The method for identifying interference in rail transit wireless communication based on array antenna according to claim 6, characterized in that: The pre-configuration of the field monitoring unit includes setting the monitoring frequency band range, resetting the radiation template and calibrating the internal electronic compass; the training of the field monitoring unit is to calculate the wave direction of all downlink signals of the useful signal network sampled by the field monitoring unit and record them in the radiation template, marking this wave direction as the partner whitelist.

8. The method for identifying interference in rail transit wireless communication based on array antenna according to claim 6, 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 white list angle value defined in the radiation template database, and the incoming wave direction signal source belonging to the white list angle value is identified as an interference signal.

9. The method for identifying interference in rail transit wireless communication based on array antenna according to claim 8, characterized in that: The sampling signal frequency information output by the comparison preprocessing module is further identified as co-channel interference or adjacent channel interference.

10. The method for identifying interference in rail transit wireless communication based on array antenna according to claim 8, characterized in that: If the frequency of the sampled signal is different from the useful signal frequency recorded in the whitelist built into the current on-site monitoring unit, the adjacent frequency interference result is directly output; 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 angle value of the incoming wave direction calculated in the previous step is inconsistent with the angle value in the whitelist, the output shows that there is co-frequency interference. 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 angle value of the incoming wave direction calculated in the previous step is consistent with the angle value in the whitelist, then interference identification analysis is performed in collaboration with the adjacent on-site monitoring unit.

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