TDOA + AOA track initiation detection method based on 5G SSB signal

Abstract

The invention relates to a 5G SSB signal-based TDOA + AOA track initiation detection method, which comprises the following steps of carrying out synchronous signal search on a reference channel and a monitoring channel, and finding out the position of an SSB peak point; eight SSB peak point phases are obtained, then phase unwrapping processing is carried out on the SSB phases of all channels, and after the unwrapped phases are averaged, target phase angle information is obtained through a virtual baseline direction finding algorithm; target echo information is extracted through distance Doppler processing, and the approximate position of a target is obtained through a TDOA algorithm; rejecting false targets by using a constant false alarm detection algorithm, and extracting target distance speed information; and finally, for the extracted target angle and distance speed information, using a track initiation algorithm to further eliminate false targets and obtain target tracks, and the method can effectively eliminate the false targets and realize accurate detection of low-altitude targets.

Description

Technical Field

[0001] The present invention belongs to the technical field of external radiation source radar target trajectory detection, and specifically relates to a TDOA+AOA track initiation detection method based on 5G SSB signals. Background Art

[0002] With the rapid development of technology, the management and safety of low-altitude airspace have become important issues in the aviation field. Especially "low, slow, and small" targets (Low and Slow Small Targets, abbreviated as LSS Targets), such as unmanned aerial vehicles, light aircraft, etc., have frequently appeared in the blind areas of airspace control in recent years, posing a severe challenge to aviation safety.

[0003] Traditional radar systems have significant limitations in monitoring low-altitude targets. Especially in complex urban environments, radar signals are easily affected by ground buildings, obstacles, etc. As a new type of radar system, external radiation source radar can effectively complement the deficiencies of traditional radars by using existing communication or broadcast signals as radiation sources. Compared with traditional active radars, external radiation source radar has the following significant advantages: (1) Passive radiation; (2) Good concealment; (3) Strong flexibility;

[0004] The electromagnetic resources that can be used by external radiation source radar in urban environments include radio broadcast signals, satellite navigation signals, radio and television signals, WIFI signals, and mobile communication signals, etc. Compared with other signals, the advantages of 5G communication signals as radar radiation sources are: (1) Wide coverage range; (2) High-precision positioning; (3) Real-time and low latency; (4) Strong anti-interference ability; (5) High-bandwidth support.

[0005] Compared with the prior art:

[0006] Technical comparison with patent CN118884377A "5G external radiation source radar detection method based on SSB signals";

[0007] First, patent CB118884377A mainly aims at the problem of 5G base station co-frequency interference. By "demodulation + modulation" to reconstruct the reference signal, it detects and reconstructs the SSB beam to avoid interference caused by the mixing of signals from multiple co-frequency base stations. While the present invention performs synchronous signal search on 5G signals, mainly for obtaining the position of the SSB peak point and calculating its phase. In order to reduce phase ambiguity, the phase of the obtained peak point is unwrapped and the phase mean value is calculated, and the extracted phase information is used with virtual baseline direction finding technology to extract target angle information.

[0008] II. Patent CB118884377A mainly focuses on improving signal quality. By means of cell search, channel estimation and reconstruction, clutter suppression and other steps, it improves the signal purity, and then enhances the detection performance. While the present invention focuses more on eliminating false targets. By extracting the target angle information and the range-velocity information extracted by the constant false alarm detection algorithm, false targets are eliminated through the track initiation algorithm to complete the accurate detection of the target trajectory.

[0009] Technical comparison of Patent CN116930941A, "An indoor multipath detection and positioning method for external radiation source radar based on 5G signals";

[0010] I. Patent CN116930941A mainly uses indoor 5G micro base stations as external radiation sources to detect and locate targets. While the present invention is mainly used for 5G base stations in urban complex environments, and the form of single radiation source and single receiving station can be used to locate the target trajectory.

[0011] II. Patent CN116930941A mainly focuses on filtering false targets in range-Doppler by constant false alarm detection to obtain the range-velocity information of real targets. While the present invention focuses on using the track initiation algorithm to eliminate false targets, that is, combining the angle information extracted in Step 2 with the range-velocity information extracted by the constant false alarm detection algorithm, and using the track initiation algorithm to further eliminate false targets to complete the accurate detection of the target trajectory. Summary of the Invention

[0012] In view of the above problems, the present invention proposes a TDOA+AOA track initiation detection method based on 5G SSB signals. Aiming at the problem that in urban complex environments, 5G base stations are densely distributed, and target detection is usually interfered by co-frequency base stations and ground obstacles, resulting in multipath clutter, which seriously interferes with the extraction of target information, it is proposed to use the target angle information extracted by the virtual baseline algorithm and the range-velocity information extracted by the constant false alarm detection algorithm as the measurement data in the external radiation source radar track initiation algorithm to achieve the accurate detection of the low-altitude target trajectory.

[0013] To achieve the above object, the technical solution adopted by the present invention is:

[0014] The TDOA+AOA track initiation detection method based on 5G SSB signals includes the following method steps:

[0015] Step S1: According to the prior information of the 5G external radiation source radar communication base station, generate the corresponding local reference signal, perform sliding cross-correlation operation on the direct wave signal and the target echo signal received by the reference channel and the monitoring channel, and find the position of the SSB peak point through maximum likelihood judgment;

[0016] Step S2: Calculate the phase of the SSB peak points for each monitoring channel, obtain the phase information of 8 SSB peak points and take the average as the phase output, and use the virtual baseline direction finding technology to obtain the target angle information;

[0017] Step S3: Combine the reference channel and the monitoring channels, extract the target information using the range-Doppler algorithm, and then use the TDOA algorithm to obtain the approximate position of the target;

[0018] Step S4: After range-Doppler processing, the target energy is already higher than the noise level. Use the constant false alarm rate detection technology to set appropriate threshold values for each unit of the range-Doppler output matrix, retain the points exceeding the threshold, and eliminate the points not reaching the threshold, so as to extract the real target information and filter out the false targets as much as possible to complete the detection of the real target;

[0019] Step S5: Combine the target angle information extracted by the virtual baseline technology and the range and speed information extracted by the constant false alarm rate algorithm, store them according to multiple frames of data, and construct the corresponding measurement data. Subsequently, perform signal processing on these data through the track initiation algorithm, calculate the motion track and its change state of the target, so as to realize the detection and tracking of the target track.

[0020] As a further improvement of the present invention, step S2 specifically includes:

[0021] After determining 8 SSB peaks in the current period, the phase of the peak points can be calculated. Assume that the true phases of N SSB peak points are φ i , i ∈ (1, 2,..., N). For any true phase φ i The wrapped phase There is:

[0022]

[0023] Among them, W is the wrapping operator, that is, make φ i plus an integer multiple of 2π to make its value between (-π, π);

[0024] Use the difference operator Δ to denote the phase difference between adjacent true phases. For φ i and There is:

[0025] Δφ i = φ i - φ i-1

[0026]

[0027] For Perform the wrapping operation on both sides:

[0028]

[0029] If the Itoh condition is satisfied:

[0030] -π ≤ Δφ i ≤ π

[0031] Then we can obtain:

[0032]

[0033] That is to say, when -π ≤ Δφ i ≤ π, the value of the difference between the re - wrapped winding phase and the true phase difference is equal. At this time, the unwrapped phase can be obtained by simply summing the differences of the winding phases, that is:

[0034]

[0035] After unwrapping the N SSB phases into continuous phases according to the above steps, the mean value of the unwrapped phases is taken as the phase output, and then the angle information of the target is obtained by using the virtual baseline direction - finding algorithm.

[0036] As a further improvement of the present invention, step S5 specifically includes:

[0037] The angle information and range - velocity information of the target can be obtained by using step 2 and step 4. The above - mentioned target information is saved as measurement data. In order to construct the track of the target, it is also necessary to define the relationship between the range and velocity of the target at the (k + 1) - th moment, where the time interval is Δt and the time parameter is k, which is defined as:

[0038] d(k + 1) = max{0, d(k)-υ max}+max{0, d(k)+υ min ·Δt - d min}

[0039] Assume that the moving speed of the target is restricted by υ max and υ min , and the moving direction of the target is described by θ. At this time, the angle change of the target is constrained by the following formula:

[0040] θ(k + 1) = max(θ min , min(θ(k)+Δθ max , θ max ))

[0041] where θ(k) is the angle of the target at time k, Δθ max is the maximum angle change per unit time of the target, and θ max and θ min are the minimum and maximum movement angle limits of the target respectively;

[0042] Assume the target speed is υ(k) and the movement angle is θ(k). The following formula is used to update the target's position:

[0043] x(k + 1) = x(k) + υ(k)·cos(θ(k))

[0044] y(k + 1) = y(k) + υ(k)·sin(θ(k))

[0045] Where y(k) and x(k) are the position coordinates of the target at time k. Each time, according to the current state of the target, the next state of the target at the next time is iteratively updated through the above formula, and finally the complete trajectory of the target can be obtained.

[0046] As a further improvement of the present invention, step S5 includes the position, speed, and angle according to the current state of the target.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] The present invention proposes a TDOA + AOA track initiation detection method based on 5G SSB signals, which uses a virtual baseline algorithm to extract target angle information and a constant false alarm detection algorithm to extract range and speed information as measurement data in the external radiation source radar track initiation algorithm to achieve precise detection of low-altitude target trajectories. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a schematic flow chart of a TDOA + AOA track initiation detection method based on 5G SSB signals of the present invention;

[0050] Figure 2 is a low-altitude detection scene diagram in a complex environment in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention but are not used to limit the scope of the present invention.

[0052] A TDOA + AOA track initiation detection method based on 5G SSB signals provided by the present invention uses a virtual baseline algorithm to extract target angle information and a constant false alarm detection algorithm to extract range and speed information as measurement data in the external radiation source radar track initiation algorithm to achieve precise detection of low-altitude target trajectories.

[0053] In this embodiment, the received signal is a 5G communication signal, and the transmission mode of the SSB signal used in the country is defined as Case C. In this mode, the base station broadcasts synchronization signals by transmitting 8 SSB signals within a 20-millisecond time period. The start symbol positions of each SSB signal are sequentially set to: 2, 8, 16, 22, 30, 36, 44, 50 (the symbol position is counted from 0), and each SSB signal occupies 4 OFDM (Orthogonal Frequency Division Multiplexing) symbols. The corresponding SSB signal index i SSB is from 0 to 7.

[0054] The following further describes the present invention in conjunction with the accompanying drawings and specific embodiments. As a specific embodiment of the present invention, the present invention provides a TDOA+AOA track initiation detection method based on 5G SSB signals. The flowchart is as Figure 1 shown, and the low-altitude detection scenario in a complex environment is as Figure 2 , and the specific steps are as follows:

[0055] Step S1: Generate a corresponding local reference signal according to the prior information of the 5G external radiation source radar communication base station, perform a sliding cross-correlation operation on the direct wave signal and the target echo signal received by the reference channel and the monitoring channel, and find the position of the SSB peak point through maximum likelihood judgment;

[0056] Step S2: The virtual baseline direction finding technology specifically includes:

[0057] After determining the 8 SSB peaks in the current period, the phase of the peak points can be obtained. Assuming that the true phases of N SSB peak points are φ i , i ∈ (1, 2,..., N), for any true phase φ i The wrapped phase is:

[0058]

[0059] where W is the wrapping operator, that is, adding an integer multiple of 2π to φ i to make its value between (-π, π).

[0060] Use the difference operator Δ to denote the phase difference between adjacent true phases. For φ i and there is:

[0061] Δφ i = φ i - φ i-1

[0062]

[0063] For both sides perform a wrapping operation:

[0064]

[0065] If the Itoh condition is satisfied:

[0066]

[0067] Then we can obtain:

[0068]

[0069] That is to say, under the condition of -π ≤ Δφ i ≤ π, the value of the difference of the wrapped phase after re-wrapping is equal to the value of the true phase difference. At this time, the unwrapped phase can be obtained by simply summing the differences of the wrapped phases, that is:

[0070]

[0071] After unwrapping the N SSB phases into continuous phases according to the above steps, the mean value of the unwrapped phases is taken as the phase output, and then the angle information of the target is obtained by using the virtual baseline algorithm.

[0072] Step S3: Combine the reference channel and the monitoring channel, and use the range-Doppler algorithm to extract the target information, and then use the TDOA algorithm to obtain the approximate position of the target;

[0073] Step S4: After range-Doppler processing, the target energy is already higher than the noise level. Use the constant false alarm rate detection technology to set appropriate threshold values for each unit of the range-Doppler output matrix, retain the points exceeding the threshold, and eliminate the points not reaching the threshold, so as to extract the true target information and filter out the false targets as much as possible to complete the detection of the true target.

[0074] Step S5: Combine the target angle information extracted by the virtual baseline technology and the range and velocity information extracted by the constant false alarm rate algorithm, store them according to multiple frames of data, and construct the corresponding measurement data. Subsequently, perform signal processing on these data through the track initiation algorithm, calculate the motion track and its change state of the target, so as to realize the detection and tracking of the target track.

[0075] Furthermore, step S5 specifically includes:

[0076] The angle information and range-velocity information of the target can be obtained by using step 2 and step 4, and the above target information is saved as measurement data. In order to construct the track of the target, it is also necessary to define the relationship between the range and velocity of the target at the k + 1 moment. Among them, the time interval is Δt, and the time parameter is k, which is defined as:

[0077] d(k + 1) = max{0, d(k) - υ max}+ max{0, d(k) + υ min ·Δt - d min}

[0078] Assume that the moving speed of the target is limited by υ max and υ min , and the moving direction of the target is described by θ. At this time, the angular change of the target can be restricted by the following formula:

[0079] θ(k + 1) = max(θ min , min(θ(k) + Δθ max , θ max ))

[0080] where θ(k) is the angle of the target at time k, and Δθ max is the maximum angular change of the target per unit time, and θ max and θ min are the minimum and maximum movement angle limits of the target respectively.

[0081] Assume that the target speed is υ(k) and the movement angle is θ(k). Use the following formula to update the position of the target:

[0082] x(k + 1) = x(k) + υ(k)·cos(θ(k))

[0083] y(k + 1) = y(k) + υ(k)·sin(θ(k))

[0084] where y(k) and x(k) are the position coordinates of the target at time k. Each time according to the current state of the target (including position, speed, angle, etc.), the state of the target at the next moment can be iteratively updated through the above formula, and finally the complete trajectory of the target can be obtained.

[0085] The above is only a preferred embodiment of the present invention, and it is not any other form of limitation to the present invention. Any modification or equivalent change made according to the technical essence of the present invention still belongs to the scope protected by the present invention.

Claims

1. A TDOA+AOA track start detection method based on 5G SSB signals, characterized in that: The method comprises the following steps: Step S1: Generate a corresponding local reference signal based on the prior information of the 5G external radiation source radar communication base station, perform sliding cross-correlation operation on the direct wave signal and the target echo signal received by the reference channel and the monitoring channel, and find the SSB peak point position through maximum likelihood judgment; Step S2, obtain the phase of the SSB peak point of each monitoring channel, obtain the phase information of 8 SSB peak points and take the average as the phase output, and use the virtual baseline direction finding technology to obtain the target angle information; Step S3, combining the reference channel and the monitoring channel, using the range Doppler algorithm to extract target information, and then using the TDOA algorithm to obtain the approximate position of the target; Step S4, after the range-Doppler processing, the target energy is already higher than the noise level, and a constant false alarm detection technique is used to set a suitable threshold value for each unit of the range-Doppler output matrix, retain the points exceeding the threshold, and eliminate the points not reaching the threshold, so as to extract the real target information and filter out the false targets as much as possible to complete the detection of the real target; Step S5: Combine the target angle information extracted by the virtual baseline technology and the distance and speed information extracted by the constant false alarm algorithm, store them according to multiple frames of data, and construct corresponding measurement data. Then, perform signal processing on these data through the track initiation algorithm to calculate the motion trajectory of the target and its change state, thereby realizing the detection and tracking of the target trajectory.

2. The TDOA+AOA track start detection method based on 5G SSB signal according to claim 1, characterized in that: Step S2 specifically includes: After determining the 8 SSB peaks in the current cycle, the phase of the peak point can be obtained. Assuming that the true phase of N SSB peak points is φ i ,i∈(1,2,...,N), for any real phase φ i Phase after wrapping have: k is an integer Among them, W is the winding operator, that is, let φ i Add integer multiples of 2π to make its value between (-π,π); Use the difference operator Δ to record the phase difference between adjacent real phases, and i and have: Df i =φ i -f i-1 right Perform twisting operation on both sides: If the Itoh condition is met: -π≤Δφ i ≤π You can get: That is to say, when -π≤Δφ i ≤π, the difference of the wrapped phase is equal to the true phase difference after re-wrapping. At this time, the unwrapped phase can be obtained by simply summing the differences of the wrapped phase, that is: After the N SSB phases are unwrapped into continuous phases according to the above steps, the average of the unwrapped phases is taken as the phase output, and then the virtual baseline direction finding algorithm is used to obtain the angle information of the target.

3. The TDOA+AOA track start detection method based on 5GSSB signal according to claim 1, characterized in that: Step S5 specifically includes: Using steps 2 and 4, the angle information and distance speed information of the target can be obtained, and the above target information is saved as measurement data. In order to construct the target track, it is also necessary to define the relationship between the distance and speed of the target at time k+1, where the time interval is Δt and the time parameter is k, which is defined as: d(k+1)=max{0,d(k)-υ max }+max{0,d(k)+υ min ·Δt-d min } Assume that the target's moving speed is υ max and min The target’s moving direction is described by θ. At this time, the target’s angle change is constrained by the following formula: θ(k+1)=max(θ min ,min(θ(k)+Δθ max ,i max )) Where θ(k) is the angle of the target at time k, Δθ max is the maximum angle change of the target per unit time, θ max and θ min are the minimum and maximum motion angle limits of the target, respectively; Assuming the target velocity is υ(k) and the motion angle is θ(k), use the following formula to update the target position: x(k+1)=x(k)+υ(k)·cos(θ(k)) y(k+1)=y(k)+υ(k)·sin(θ(k)) Where y(k) and x(k) are the position coordinates of the target at time k. Each time according to the current state of the target, the state of the target at the next moment is iteratively updated through the above formula, and finally the complete trajectory of the target can be obtained.

4. The TDOA+AOA track start detection method based on 5GSSB signal according to claim 3, characterized in that: Step S5 includes position, speed and angle according to the current state of the target.

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