Active and passive coordinated sensing fusion method for radar communication dual-function system

Abstract

The present invention discloses an active and passive coordinated sensing fusion method for a radar communication dual-function system. The method includes: step 1 embedding a dedicated sensing symbol in a signal transmitted by a base station; step 2 solving a power allocation problem using an optimization problem; step 3 having a receiving access point receive a passive sensing signal and process direct path interference into white noise using a whitening filter; step 4 having the receiving access point determine whether a target is present using a generalized likelihood ratio test detector, and then the receiving access point and base station transmit the binary determination result and target detection probability to a fusion center; and step 5 having the fusion center vote and aggregate the received information to determine whether a target is present. The present invention can improve the accuracy and efficiency of target detection, positioning and acquisition of environmental information, and reconstruction, and has the potential to significantly improve the performance of wireless communication sensing networks.

Description

[Technical Field]

[0001] This invention belongs to the field of radar power distribution and, in particular, to an active and passive coordinated sensing fusion method for radar communication dual-function systems. [Background technology]

[0002] Communication systems are evolving from 5G to 6G, presenting unique challenges for networks pursuing global coverage, green intelligence, sensing interconnection, and the convergence of communication and sensing. To fully realize the potential of 6G, it is necessary to acquire environmental sensing information, enable seamless information interaction and sharing, and intelligently control information processing. Therefore, dual-function radar communication, abbreviated as DFRC, is being pursued by researchers who see the integration of communication systems and radar sensors as a key technology for 6G and are driving research into DFRC systems. However, there are several problems with DFRC system research. On the one hand, fading and interference characteristics of wireless communication systems cause uncertainty in sensing, and data received by a single radar may not be perfect. On the other hand, DFRC research mainly focuses on waveform design and signal processing, with little consideration given to multi-static sensing capabilities, resulting in wasted sensing resources. [Overview of the Initiative] [Problems that the invention aims to solve]

[0003] The object of the present invention is to provide an active and passive coordinated sensing fusion method for a radar communication dual-function system that integrates active and passive sensing into a DFRC system to improve the efficiency of sensing resources. [Means for solving the problem]

[0004] Regarding the technical solution, the present invention provides an active and passive coordinated sensing fusion method for a dual-function radar communication system, wherein the dual-function radar communication system includes a dual-function radar communication base station (BS) and receiving access points (RAPs) equipped with a fusion center (FC), the dual-function radar communication base station (BS) communicates with the user while performing active sensing, and the receiving access points (RAPs) perform passive sensing and are subject to direct path interference of signals transmitted by the dual-function radar communication base station (BS), the receiving access points (RAPs) and the dual-function radar communication base station (BS) are connected via a backhaul link, but the link capacity is limited and therefore does not support the transmission of large amounts of data, and the method is Step 1 involves embedding a dedicated sensing symbol into the signal transmitted by a dual-function radar communication base station (BS) and precoding it using a zero-forcing radar beamformer. Step 2 involves modeling the optimization problem to maximize the average target detection probability, ensuring that the total transmission power does not exceed the budget of the dual-function radar communication base station (BS) and that the user's signal-to-interference-to-noise ratio (SINR) meets the minimum requirements, and solving it using a power distribution algorithm based on a traversal algorithm. Step 3 involves the receiving access points (RAPs) receiving passive sensing signals from the dual-function radar communication base station (BS) to the target and then to the receiving access points (RAPs), and using a whitening filter to process direct path interference in the passive sensing signals into white noise. Step 4 involves the receiving access points (RAPs) determining whether a target is present using a Generalized Likelihood Ratio Test (GLRT) detector, and the receiving access points (RAPs) and dual-function radar communication base stations (BS) transmitting the determination result and target detection probability to the fusion center (FC). The Fusion Center (FC) includes step 5, which aggregates votes on the received information and determines whether or not a target exists.

[0005] Furthermore, in step 1, specifically, the dedicated sensing symbol is s0, which is pre-coded using a zero-forcing radar beamformer, and the pre-coding vector is as follows:

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[0006] Furthermore, the optimization problem described in step 2 is shown as follows:

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[0007] Furthermore, in step 2, the step of using the power distribution algorithm based on the traversal algorithm is specifically When the power p0 allocated by the sensing symbol gradually increases and satisfies the power budget of the BS, the simultaneous detection probability

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[0008] Furthermore, in step 3, specifically When the target exists, the passive sensing signal received by the r - th RAP is as follows

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[0009] Furthermore, in step 4, specifically, The binary assumption of the GLRT detector after using the whitening filter is as follows:

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[0010] Furthermore, in Step 5, specifically, FC makes the following binary assumptions:

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[0011] In terms of beneficial effects, the present invention has the following significant advantages compared to the prior art. By employing the above technical solutions, the present invention integrates active and passive sensing into the DFRC system compared to the prior art, improving the accuracy and efficiency of target detection, and significantly improving its sensing performance compared to a DFRC system that uses only passive sensing. Furthermore, the binary judgment result voting aggregation solution can solve the enormous overhead problem caused by direct transmission of sensing signals to the fusion center, potentially significantly improving the performance of the wireless communication sensing network. [Brief explanation of the drawing]

[0012] [Figure 1] This is a model diagram of the DFRC system of the present invention. [Figure 2] This is a flowchart of the method of the present invention. [Figure 3] This figure shows the relationship between the average detection probability and the number of RAPs provided by the embodiments of the present invention. [Modes for carrying out the invention]

[0013] The technical solutions of the present invention will be further described below with reference to the drawings.

[0014] The technical problem that the embodiments of the present invention aim to solve is to provide an active and passive coordinated sensing fusion method for a radar communication dual-function system that integrates active and passive sensing into a DFRC system to improve the efficiency of sensing resources.

[0015] As shown in Figure 1, the multi-input multi-output dual-function radar communication base station (MIMO DFRC BS) described in this example has a convergence center (FC) that performs active sensing while communicating with the user, and receiving access points (RAPs) that perform passive sensing. The RAPs and BS are connected via a backhaul link, but due to the limited link capacity, it cannot handle the transmission of large amounts of data.

[0016] Figure 2 is a flowchart of an active and passive coordinated sensing fusion method for a radar communication dual-function system provided by an embodiment of the present invention, which is: Step 1 involves embedding a dedicated sensing symbol into the signal transmitted by the BS and precoding it using a zero-forcing radar beamformer. Step 2 involves modeling the optimization problem to maximize the average target detection probability, ensuring that the total transmitted power does not exceed the BS budget and that the user's signal-to-interference-to-noise ratio (SINR) meets the minimum requirements, and solving it using a power distribution algorithm based on a traversal algorithm. RAPs receive passive sensing signals and process direct-path interference (DPI) into white noise using a whitening filter in step 3. Step 4 involves RAPs determining whether a target is present or not using a Generalized Likelihood Ratio Test (GLRT) detector, and then RAPs and BS transmitting the binary determination result and target detection probability to FC. FC includes step 5, which involves aggregating votes on the received information and determining whether or not a target exists.

[0017] In the embodiment, the dedicated sensing symbol in step 1 is s0, which is precoded using a zero-forcing radar beamformer, and the precode vector is as follows:

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[0018] In the example, the optimization problem in step 2 is shown as follows:

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[0019] In the embodiment, as p0 gradually increases and satisfies the power budget of BS,

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[0020] (1) p'0 = P T Δp, p sum Initialize as =p'0, (2) Set p0 = p'0 - Δp, (3) Convex optimization problem min||p||1s.t.γ using the CVX toolkit k Solve ≥Γ, (4)p sum Set p =||p||1 and p'0 = p0, (5)p sum ≥P T If true, proceed to step (2); otherwise, output p.

[0021] In the embodiment, in step 3, if a target is present, the passive sensing signal received by the r-th RAP is as follows:

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[0022] In the examples, the binary assumption of the GLRT detector after using the whitening filter is as follows:

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[0023] In the example, in step 5, FC makes the following binary assumption:

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[0024] In this example, 10,000 samples are prepared for the simulation. The DFRC system parameters are set as follows:

[0025] [Table 1]

[0026] This example, as one specific case of the embodiment of the present invention, can be extended to other similar cases.

[0027] Figure 3 shows the relationship between the average detection probability and the number of RAPs. A change in the average detection probability is observed when the gain variance of the combined sensing channels is -37 / -36 / -35dB (-37dB, -36dB, and -35dB in the legend of the figure). When the gain variance of the combined sensing channels is -36dB or greater, the average detection probability increases with the increase in RAPs, but the rate of increase when the gain variance of the combined sensing channels is -35dB is much greater than the rate of increase when the gain variance of the combined sensing channels is -36dB. Furthermore, when the gain variance of the combined sensing channels is -37dB, the average detection probability hardly increases with the increase in RAPs and tends to always remain at 0. This is because the binary reasoning results of the FC are obtained through vote aggregation in a limited backhaul capacity scenario, and this vote aggregation focuses on the quality of the sensing signal of each individual RAP. Therefore, as the gain variance of the combined sensing channels increases, the detection probability of a single RAP increases. Furthermore, as the number of RAPs increases, the probability of misjudgment after vote aggregation decreases even further.

[0028] Although the present invention and its embodiments have been schematically described above, this description is not limited thereto, and the illustrations represent only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, any structural form and embodiment similar to a technical solution designed by a person skilled in the art, without departing from the spirit of the invention and without creativity, should all be included within the scope of protection of the present invention.

Claims

1. An active and passive coordinated sensing fusion method for a radar communication dual-function system, wherein the radar communication dual-function system includes a dual-function radar communication base station (BS) and receiving access points (RAPs) equipped with a fusion center (FC), the dual-function radar communication base station (BS) communicates with a user while performing active sensing, the receiving access points (RAPs) perform passive sensing and are subject to direct path interference of signals transmitted by the dual-function radar communication base station (BS), the receiving access points (RAPs) and the dual-function radar communication base station (BS) are connected via a backhaul link, and the method is as follows: Step 1 involves embedding a dedicated sensing symbol into the signal transmitted by a dual-function radar communication base station (BS) and precoding it using a zero-forcing radar beamformer. Step 2 involves modeling the optimization problem to maximize the average target detection probability, ensuring that the total transmission power does not exceed the budget of the dual-function radar communication base station (BS) and that the user's signal-to-interference-to-noise ratio (SINR) meets the minimum requirements, and solving it using a power distribution algorithm based on a traversal algorithm. Step 3 involves the receiving access points (RAPs) receiving passive sensing signals from the dual-function radar communication base station (BS) to the target and then to the receiving access points (RAPs), and using a whitening filter to process direct path interference in the passive sensing signals into white noise. Step 4 involves the receiving access points (RAPs) determining whether a target is present using a Generalized Likelihood Ratio Test (GLRT) detector, and the receiving access points (RAPs) and dual-function radar communication base stations (BS) transmitting the determination result and target detection probability to the Fusion Center (FC). A method characterized by comprising step 5, in which a fusion center (FC) aggregates votes on the received information and determines whether or not a target exists.

2. In step 1, specifically, the dedicated sensing symbol is s ０ Therefore, precoding is performed using a zero-forcing radar beamformer, and the precoded vector is as follows: [Number 42] Here, H = [h １ , h ２ , . . . , h Ｋ ] Ｈ is the communication channel matrix, a(θ) is the transmit steering vector, θ is the azimuth angle of the target relative to BS, and the operator [Number 43] The active and passive coordinated sensing fusion method for a radar communication dual-function system according to claim 1, characterized in that represents a two-norm operation.

3. The optimization problem described in Step 2 is shown as follows: [Number 44] Here, [Number 45] This is the simultaneous detection probability, [Number 46] Here, R is the target detection probability for BS and RAPs, and R is the number of RAPs. [Number 47] This is the noncentral chi-squared cumulative distribution function with 2 degrees of freedom, and ρ ｒ ξ are the non-central parameters of BS and RAPs, and may be given according to the generalized likelihood ratio test detector used. ｒ These are the thresholds for the BS and RAPs detectors. [Number 48] This is the SINR of the i-th user, [Number 49] is a normalized communication transmission pre-code vector, λ is a regularization parameter, and p = [p ０ , p １ ,..., p Ｋ is the power distribution of sensing symbols and communication symbols, [Number 50] Γ is the variance of additive white Gaussian noise (AWGN), K is the number of users, Γ is the required SINR threshold, and P Ｔ The active and passive coordinated sensing fusion method for a radar communication dual-function system according to claim 1, characterized in that the power budget is BS.

4. Step 2 involves using a power distribution algorithm based on a traversal algorithm, specifically, Power p allocated by sensing symbol ０ As it gradually increases and meets the BS power budget, the probability of simultaneous detection [Number 51] It gradually increased, p' ０ = P Ｔ Δp, p ｓｕｍ = p' ０ Initialize as follows, and here, p' ０ The initial parameters are set, Δp is the step size, and p ｓｕｍ Step 2.1, where the determination condition is, p ０ = p' ０ Step S2.2 sets -Δp, Using the CVX toolkit to solve the convex optimization problem min||p|| １ s.t. γ ｋ Solve ≥Γ, || || １ Step 2.3 is the norm, p ｓｕｍ = ||p|| １ , p' ０ = p ０ Step 2.4 is to set it as follows, p ｓｕｍ An active and passive coordinated sensing fusion method for a radar communication dual-function system according to claim 1, comprising: step 2.5, if ≥ PT, proceed to step 2.2; otherwise, output p.

5. In step 3, specifically, If a target exists, the passive sensing signal received by the r-th RAP is as follows: [Number 52] Here, n' ｒ [l] represents the AWGN matrix, α ｒ The gain of the combined sensing channels is b(φ ｒ ) is the steering vector of the receiving antenna, and φ ｒ is the azimuth angle of the target relative to the r-th RAP, and X = WS is the DFRC signal matrix. [Number 53] S=[s ０ ,s １ , . . , s Ｋ ], s ｉ i = 1, 2, ..., K is the communication symbol of the i-th user, G ｒ This shows the targetless channel between BS and the r-th RAP when no target is present, and the signal is obtained by passing it through a matched filter and vectorizing it. [Number 54] Here, B ｒ = b(φ ｒ ) a Ｈ (θ), W = WW Ｈ , vec() indicates the vectorization operator, ε ｒ It is a complex Gaussian distribution with a zero mean, and the block covariance matrix... [Number 55] It has, Here, [Number 56] Whitening filter decomposed by Cherosky [Number 57] The method for active and passive coordinated sensing fusion for a radar communication dual-function system according to claim 1, characterized in that it obtains the following.

6. In step 4, specifically, The binary assumption of the GLRT detector after using the whitening filter is as follows: [Number 58] Here, d(φ ｒ θ) = vec(B ｒ W) Next, the corresponding GLRT detector is given by the following equation: [Number 59] The joint probability density function of the received signal is given by the following calculated test statistic: [Number 60] The method for active and passive coordinated sensing fusion for a radar communication dual-function system according to claim 1, characterized in that a binary determination is then performed according to (8).

7. In step 5, specifically, FC makes the following binary assumptions: [Number 61] Here, D ｒ These are the binary inference results for BS and the i-th RAP, respectively, and D ｒ =0 indicates that the target does not exist, D ｒ = 1 indicates that a target exists, n represents the voting threshold, and n is given by the following equation: [Number 62] The active and passive coordinated sensing fusion method for a radar communication dual-function system according to claim 1, characterized in that is the false alarm probability of BS and RAPs.

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