Multi-network target perception system and perception method thereof

Abstract

The embodiment of the present invention discloses a multi-network target perception system and a perception method thereof, wherein the perception system includes a plurality of inter-sensory base stations, each of which is arranged on the same horizontal plane, and each of which periodically sends signals around. When a certain base station detects the appearance of a target, other base stations around the base station continuously detect the target appearance area. The system obtains the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station, calculates the target position according to the obtained vertical arrival angle and horizontal arrival angle, and obtains the target's speed according to the change in the frequency of the target's transmitted signal; then, the target's movement direction is obtained by using the change in the target position information under two perception cycles of the base station, and the perception of the target position information and motion information is completed. The perception of the present invention is more reliable, and the signal processing process is optimized, so that the delay of processing signals is greatly reduced, and the performance of the system for simultaneous communication is improved.

Description

Technical Field

[0001] The present invention relates to the field of 5G communications, and in particular to a multi-network target perception system and a perception method thereof. Background Art

[0002] In future mobile communication systems, higher frequency bands (millimeter wave and even terahertz), wider bandwidths, and larger-scale antenna arrays will make high-precision and high-resolution perception possible, thereby realizing Integrated Sensing and Communication (ISAC) in one system and integrating communication and perception functions.

[0003] The perception algorithms currently used are:

[0004] One method is to obtain the perceived target information from the received signal by exhaustive method. Since the arrival angle information and Doppler frequency of the received signal reflected by the target can be accurately obtained when the position information and motion information of the perceived target are known, after the Doppler frequency deviation and arrival angle are obtained by processing the signal obtained by the receiver, the position and speed of the target to be perceived can be obtained by reverse exhaustive method using the estimation matrix, and the accuracy is verified by bringing it into the monitoring model matrix again.

[0005] In addition, the received signal strength indicator (RSSI) is often used to detect whether a link is blocked. The RSSI of a known communication link is continuously monitored, and when the RSSI changes suddenly, it is determined that the link is blocked or the link direction has changed. Furthermore, a deep learning algorithm is introduced to quickly determine the best link direction, and when the best link direction changes, it is predicted that a blockage will occur, which significantly improves the efficiency and reliability of using RSSI to detect link blockage.

[0006] In the above algorithms, the reverse exhaustive method can only obtain a good confidence level by setting the position information and motion information thresholds when the target moves in a small range. There is false detection for the perception of targets in a large range, and the complexity of signal processing and calculation also increases the perception delay. The algorithm using RSSI is based on channel state information (CSI), and its defect is that it cannot accurately distinguish between link interruptions caused by link movement and link obstruction. Summary of the invention

[0007] The technical problem to be solved by the embodiments of the present invention is to provide a multi-network target perception system and a perception method thereof, so as to realize the perception function in communication.

[0008] In order to solve the above technical problems, an embodiment of the present invention proposes a multi-network target perception system, wherein the perception system includes a plurality of inter-sensory base stations, each of which is arranged on the same horizontal plane, and each of which periodically sends signals around. When a base station detects the appearance of a target, other base stations around the base station continuously detect the target appearance area.

[0009] The system obtains the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station, calculates the target position based on the obtained vertical arrival angle and horizontal arrival angle, and obtains the target speed based on the change in the target's transmitted signal frequency; then uses the change in the target position information under two sensing cycles of the base station to obtain the target's movement direction, thereby completing the perception of the target position information and movement information.

[0010] Accordingly, an embodiment of the present invention further provides a perception method of a multi-network target perception system, comprising:

[0011] Target position sensing step: obtain the vertical arrival angle and horizontal arrival angle of the target's transmission signal to each base station, and calculate the target position based on the obtained vertical arrival angle and horizontal arrival angle;

[0012] Target movement perception steps: obtain the target speed based on the change in the target's transmission signal frequency; then use the change in the target position information under two sensing cycles of the base station to obtain the target's movement direction, and complete the perception of the target's position information and movement information.

[0013] The beneficial effects of the present invention are as follows: the present invention uses the arrival angle to obtain the perceived target position information through the multi-network of base station receivers. The target position determined by the intersection of multiple links in the present invention is more reliable than the traditional single base station perception, and the signal processing process is optimized, so that the delay of processing signals is greatly reduced, and the performance of the system for simultaneous communication is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a perception schematic diagram of a multi-network target perception system according to an embodiment of the present invention.

[0015] Figure 2 It is a schematic diagram of the perception process of the multi-network target perception system according to an embodiment of the present invention.

[0016] Figure 3 It is a geometric model of a multi-network target perception system composed of two inter-sensory base stations in an embodiment of the present invention.

[0017] Figure 4 It is a structural diagram of a dual-base station link warning according to Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0018] It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present invention is further described in detail below in conjunction with the drawings and specific embodiments.

[0019] In the embodiments of the present invention, if there are directional indications (such as up, down, left, right, front, back, etc.), they are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0020] In addition, in the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0021] Please refer to Figure 1-2 The multi-network target perception system of the embodiment of the present invention includes several inter-sensory base stations.

[0022] The present invention utilizes a plurality of receivers for joint networking and completes target perception by processing the arrival angle information. The integrated base stations of the present invention are arranged on the same horizontal plane, and each integrated base station periodically sends signals around. When a base station detects the appearance of a target, other base stations around the base station continuously detect the target appearance area to achieve synchronization of perception. When a traditional single base station is performing perception and communication, it is necessary to process the received signal and obtain the target's location information and motion information through the corresponding perception algorithm.

[0023] The system obtains the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station, calculates the target position based on the obtained vertical arrival angle and horizontal arrival angle, and obtains the target speed based on the change in the target's transmitted signal frequency; then uses the change in the target position information under two sensing cycles of the base station to obtain the target's movement direction, thereby completing the perception of the target position information and movement information.

[0024] like Figure 3 , Figure 3 It is a simple geometric model of a target perception system consisting of two integrated base stations.

[0025] With the position of base station 1 as the origin and the line connecting the two base stations as the y-axis, a spatial rectangular coordinate system is constructed as shown in the figure. The distance between base station 1 and base station 2 is known, denoted as d.

[0026] Through geometric relationships, the target coordinates should be:

[0027] ;

[0028] in, , , , are the vertical arrival angle and horizontal arrival angle from the target to base station 1 and base station 2 respectively.

[0029] Perform cross ambiguity function processing on the received signal and the transmitted reference signal.

[0030]

[0031] in represents the conjugate operation, Indicates receiving signal, represents the base station transmitting the reference signal, τ is the distance, f d is the Doppler frequency shift, and T is the OFDM symbol period. It can be observed that when and match and When the delay and Doppler shift between The peak value of the ambiguity function is saved, and the Doppler frequency deviation and beam direction corresponding to the maximum value of the ambiguity function are saved.

[0032] The vertical and horizontal angles of arrival from the target to the base station can be obtained through the beam direction. Since the base station location information is known, the specific location of the perceived target can be identified in the networking space. The speed of the perceived target can be obtained by processing the Doppler frequency deviation, and then the target's movement direction can be obtained by using the changes in the target position information under two sensing cycles of the base station, completing the perception function of the target position information and motion information.

[0033] The perception method of the multi-network target perception system of the present invention includes a target position perception step and a target operation perception step.

[0034] Target position perception steps: obtain the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station, and calculate the target position based on the obtained vertical arrival angle and horizontal arrival angle.

[0035] Target movement perception steps: obtain the target speed based on the change in the target's transmission signal frequency; then use the change in the target position information under two sensing cycles of the base station to obtain the target's movement direction, and complete the perception of the target's position information and movement information.

[0036] As an implementation method, the coordinates of the target are calculated according to the following formula:

[0037] ;

[0038] in, , , , are the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to the two base stations, and d is the distance between the two base stations that receive the target's transmitted signal.

[0039] The received signal is processed by cross ambiguity function to obtain the beam direction with the strongest received signal and the corresponding Doppler frequency deviation. The vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station are obtained according to the beam direction. The speed of the target is obtained according to the Doppler frequency deviation. The ambiguity function processing formula is as follows:

[0040] ;

[0041] in represents the conjugate operation, Indicates receiving signal, represents the base station transmitting the reference signal, τ is the distance, f d is the Doppler frequency shift, and T is the OFDM symbol period.

[0042] Example 1, dual-base station link warning:

[0043] like Figure 4 As shown, the scanning of the beam is used to sense the moving obstruction and issue a warning when communication interruption is about to occur, that is, the moving obstruction blocks the line of sight (LOS) link of the reference signal, so that the receiver can take measures such as link change in advance to keep the communication unobstructed.

[0044] Example 2, millimeter wave gesture recognition:

[0045] Taking advantage of the high distance resolution and angle resolution of millimeter-wave radar, multiple groups of millimeter-wave radars can be used to sense the Doppler frequency deviation caused by gesture changes, and then trained with a deep learning neural network to make the recognition more detailed and reliable.

[0046] Embodiment 3, motion trajectory estimation:

[0047] By real-time perception of the target's position and motion information through multiple networks, the target's motion trajectory is mapped and an estimate of the target's future motion trajectory is made. The multi-network arrival angle perception scheme of the present invention can effectively reduce the perception delay and improve the precision and accuracy of perception.

[0048] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-network target perception system, characterized in that: The sensing system includes a plurality of inter-sensory base stations, each of which is arranged on the same horizontal plane. Each of the inter-sensory base stations periodically sends signals around. When a base station detects the appearance of a target, other base stations around the base station continuously detect the area where the target appears. The system obtains the vertical arrival angle and horizontal arrival angle of the target's transmission signal to each base station, calculates the target position based on the obtained vertical arrival angle and horizontal arrival angle, and obtains the target speed based on the change in the frequency of the target's transmission signal; then uses the change in the target position information under two sensing cycles of the base station to obtain the target's movement direction, and completes the perception of the target's position information and movement information; The system calculates the coordinates of the target according to the following formula: ； in, , , , are the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to the two base stations, and d is the distance between the two base stations that receive the target's transmitted signal.

2. The multi-network target perception system according to claim 1, characterized in that: The system performs cross ambiguity function processing on the received signal to obtain the beam direction with the strongest received signal and the corresponding Doppler frequency deviation, obtains the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station according to the beam direction, and obtains the target's speed according to the Doppler frequency deviation, wherein the ambiguity function processing formula is as follows: ； in represents the conjugate operation, Indicates receiving signal, represents the base station transmitting reference signal, τ is the receiving delay of the echo signal, and f d is the Doppler frequency shift, and T is the OFDM symbol period.

3. A perception method of a multi-network target perception system as claimed in any one of claims 1 to 2, characterized in that: The method comprises: Target position sensing step: obtain the vertical arrival angle and horizontal arrival angle of the target's transmission signal to each base station, and calculate the target position based on the obtained vertical arrival angle and horizontal arrival angle; Target movement perception steps: obtain the target speed according to the change of the target's transmission signal frequency; then use the change of the target position information in two sensing cycles of the base station to obtain the target's movement direction, and complete the perception of the target's position information and movement information; In the target position sensing step, the coordinates of the target are calculated according to the following formula: ； in, , , , are the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to the two base stations, and d is the distance between the two base stations that receive the target's transmitted signal.

4. The sensing method of the multi-network target sensing system according to claim 3, characterized in that: In the target position sensing step, the received signal is subjected to cross ambiguity function processing to obtain the beam direction with the strongest received signal and the corresponding Doppler frequency deviation, and the vertical arrival angle and horizontal arrival angle of the target's transmitted signal to each base station are obtained according to the beam direction, and the speed of the target is obtained according to the Doppler frequency deviation, wherein the ambiguity function processing formula is as follows: ； in represents the conjugate operation, Indicates receiving signal, represents the base station transmitting reference signal, τ is the receiving delay of the echo signal, and f d is the Doppler frequency shift, and T is the OFDM symbol period.

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