Radar communication and perception integrated concealment communication method and system

Abstract

The application relates to a concealed communication method based on radar communication and perception integration, which comprises the following steps: constructing a corresponding communication model according to a communication system, and describing a communication expression; constructing a perception model according to the communication system, deducing a false alarm probability and a detection probability, simultaneously constructing a listening model, describing a listening expression, and deducing a KL divergence; and maximizing a signal-to-noise ratio of communication by optimizing a beamforming vector of a radar transmitter, so as to improve the performance of communication. The application can more effectively ensure safety and high-speed transmission.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and specifically to a covert communication method and system based on radar-communication-sensing integration. Background Technology

[0002] With the continuous development of mobile communication technology, the demand for network communication systems is also increasing. To meet this demand, a new concept has emerged in the field: integrated communication and sensing. In radar, the sensing function needs to identify targets, while the communication function needs to ensure secure information transmission. Combining the two can make the radar more powerful. Integrating communication and sensing functions into a single transmitter has many advantages. First, integration can reduce costs, decrease the complexity of the radar system, improve system efficiency, and reduce the number of parts. Second, integration can reduce space occupation, improve system reliability, and contribute to improved system performance. Finally, integration can provide more functions and offer users more comprehensive services.

[0003] Covert communication refers to a method of transmitting information by hiding or concealing its content, typically used to prevent certain information from being discovered or detected by others. Covert communication technology can help users transmit private and important information without being discovered by third parties, thus achieving the purpose of concealment. Covert communication technology can be divided into three categories: 1. Encrypted communication: Encryption technology is used to encrypt information during transmission, so that the information cannot be decrypted by third parties during transmission; 2. Covert transmission: Special techniques are used to conceal or hide information during transmission, so that the information cannot be identified by third parties during transmission; 3. Wireless transmission: Wireless signals are used to transmit information during transmission, so that the information cannot be discovered by third parties during transmission. The field of covert communication has always attracted attention, and researchers are actively exploring new technologies to improve the security and reliability of covert communication to achieve more secure transmission results. For example, intelligent covert communication technology can analyze the user's behavioral characteristics and automatically determine the appropriate transmission method based on different user environments and situations to improve transmission security. In addition, covert communication technology based on distributed multicast can also effectively transmit private information to multiple receivers to reduce transmission risks. Covert communication technology is an important technology that can meet the needs of user groups with special requirements in terms of security and reliability, such as government agencies, military institutions, and financial institutions.

[0004] With the development of wireless network technology, the field of integrated communication and sensing based on covert communication transmission has become an important research area. Currently, the application of wireless transmission technology allows covert communication transmission to transmit information more effectively, especially for signal transmission in wireless environments. In this context, integrated communication and sensing technology based on covert communication transmission will become even more crucial. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a covert communication method and system based on radar communication and sensing integration, in order to solve the above problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A covert communication method based on radar-communication-sensing integration includes the following steps:

[0008] Construct a corresponding communication model based on the communication system and describe the communication expression;

[0009] Based on the communication system, a perception model is constructed, and the false alarm probability and detection probability are derived. At the same time, a listening model is constructed, the listening expression is described, and the KL divergence is derived.

[0010] By optimizing the beamforming vector of the radar transmitter, the signal-to-noise ratio of the communication is maximized, thereby improving the communication performance.

[0011] Furthermore, the communication model is specifically as follows:

[0012]

[0013] In the formula y b,l This represents the received signal at the base station, where l represents the time slot and x represents the received signal at the base station. l This represents the transmission signal of the device in the l-th time slot, i.e., the dual-function signal, w. r This represents the beamforming vector during radar transmission. Let z be the channel vector between the radar and the legitimate receiver user, where H represents the conjugate transpose operation, and the signal follows a Rayleigh flat fading channel; b,l The additive white Gaussian noise at the legitimate receiver user has a mean of 0 and a variance of . The complex Gaussian distribution, i.e. s l This indicates the signal transmitted before radar beamforming. Where E represents the expectation, expressed as P = ||x|| 2 =||w r || 2 Let ||·|| represent the transmit power of the transmitter radar, where ||·|| 2 This indicates the calculation of the square of the L2 norm.

[0014] Furthermore, the perception model is specifically as follows:

[0015] The received signal y at the radar r,l for:

[0016]

[0017] Where H0 indicates that there is no target at the destination of the radar scan, and H1 indicates that there is a target at the destination of the radar scan; α0 represents channel attenuation; a t (θ) and a r (θ) represent the transmit steering vector and the receive steering vector, respectively, and the two are equal; z r,l This indicates the noise at the radar location.

[0018] Furthermore, the false alarm probability and detection probability are derived, and a listening model is constructed to describe the listening expression and derive the KL divergence, specifically as follows:

[0019] The channel attenuation and angle will be estimated by maximum likelihood estimation, and the corresponding threshold will be determined by generalized likelihood ratio test.

[0020] For radar detection signals, the false alarm probability P FA for

[0021] P FA =exp(-τ / 2σ) r 2 )

[0022] Where τ represents the radar detection threshold;

[0023] Detection probability P D for

[0024]

[0025] In case H1, the received signal at the radar is represented by a chi-square distribution, where ρ represents the non-central parameter in the corresponding chi-square distribution, and P D It increases monotonically with the increase of this non-central parameter; Γ represents the gamma function;

[0026] Using the watchman's listening model, we can represent the watchman's received signal y. w for:

[0027]

[0028] in, This represents the channel coefficient at which the radar reaches the watcher; z w This indicates the noise at the radar location. In this context, H0 indicates that the radar did not send a signal, and therefore the watcher did not receive a signal; H1 indicates that the radar sent a signal, and therefore the watcher received a signal.

[0029] Using this listening signal expression, the corresponding symmetric KL divergence is obtained as follows:

[0030]

[0031] Here, tr represents the trace of the matrix.

[0032] Furthermore, the improvement of communication performance by optimizing the beamforming vector of the radar transmitter to maximize the signal-to-noise ratio is specifically as follows:

[0033]

[0034]

[0035] P≤P max ,

[0036] P D ≥Γ,

[0037] Where, γ b f0 represents the signal-to-noise ratio at the legitimate receiver. L and F1 L Let P represent the likelihood function for two scenarios where the guard is listening to the signal, ò represent the concealment coefficient, and P represent the likelihood function for two scenarios. max Γ represents the maximum transmit power, and Γ represents the minimum detection probability of the radar;

[0038] The optimization is performed using a positive semidefinite relaxation method. Finally, the result is obtained by determining whether the rank of the matrix is ​​one. If the rank is one, the matrix is ​​directly decomposed; otherwise, Gaussian randomization is performed.

[0039] A covert communication system based on radar-communication-sensing integration includes a transmitter radar, a legitimate receiver user, a target, and a watcher. The transmitter radar combines sensing and communication signals into a dual-function signal and transmits it to both the target and the legitimate receiver user. The watcher monitors the communication between the transmitter radar and the legitimate receiver user. By optimizing the beamforming vector at the transmitter radar, secure communication is achieved while simultaneously sensing the presence of the target.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] This invention considers using false alarm probability and detection probability in the radar perception model to evaluate radar performance, and also considers using symmetric KL divergence at the watcher's location to evaluate its listening performance, which can more effectively ensure security and high-speed transmission. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the system structure of the present invention;

[0043] Figure 2 This is a comparison chart of simulation results and numerical results for false alarm rate and missed detection rate in one embodiment of the present invention.

[0044] Figure 3 This is a simulation diagram of the concealment rate with respect to different concealment coefficients under different transmission powers in one embodiment of the present invention;

[0045] Figure 4 This is a simulation diagram of the concealment rate of different watchers (Willy) with different numbers of radar antennas under one embodiment of the present invention. Detailed Implementation

[0046] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0047] Please refer to Figure 1 This invention provides a covert communication system based on radar, communication and sensing integration, which consists of a transmitter radar, a legitimate receiver user, a target and a watcher. The transmitter radar combines communication signals and sensing signals to form a dual-function signal, which is then transmitted to the target and the legitimate receiver user. At the same time, the watcher can also acquire this dual-function signal.

[0048] In this embodiment, the system consists of a radar equipped with N antennas, a watcher with M antennas, and a legitimate receiver user with only one antenna. The radar aims to be detected by the watcher with the lowest possible probability and to conduct covert communication with the legitimate receiver user.

[0049] The communication model from radar to a legitimate receiver user can be represented as:

[0050]

[0051] In the formula y b,l This represents the received signal at the base station, where l represents the time slot and x represents the received signal at the base station. l This represents the transmitted signal of the device in the l-th time slot, i.e., the dual-function signal, and x = w r s, Let z be the channel gain vector between the radar and the user, and let z be the signal that follows a Rayleigh flat fading channel. b,l The additive white Gaussian noise at the legitimate receiver user has a mean of 0 and a variance of . The complex Gaussian distribution, i.e. Where, P = ||x|| 2 =||w r|| 2 This indicates the transmit power of the transmitter radar.

[0052] Using the radar's sensing model, this invention can represent the received signal y at the radar. r,l for:

[0053]

[0054] Where H0 indicates that there is no target at the destination of the radar scan, and H1 indicates that there is a target at the destination of the radar scan. α0 represents channel attenuation. t (θ) and a r (θ) represents the transmit steering vector and the receive steering vector, respectively. r,l This indicates the noise at the radar location.

[0055] Next, we will estimate the channel attenuation and angle using maximum likelihood estimation. Maximum likelihood estimation is an efficient method for estimating radar detection angle and attenuation coefficients. It solves for these parameters by building a model and calculating the maximum likelihood between the model and the observations. Maximum likelihood estimation can be used to estimate radar detection angle and attenuation coefficients, as well as to determine the optimal detection strategy.

[0056] Then, the generalized likelihood ratio check (GLP-Q) is applied to determine the corresponding threshold. GLP-Q is an effective technique for detecting weak signals and can be used in radar technology. It determines the validity of a signal by comparing the likelihood ratios of the hypotheses and counter-hypotheses. It can identify the signal source and use its characteristics for identification and tracking. It can also be used to resist noise interference and maintain a low probability detection rate.

[0057] Generalized likelihood ratio (GLR) check and maximum likelihood estimation (MLE) can be used to estimate radar detection probabilities. GLR check compares the likelihood ratios of the hypotheses and counter-hypotheses to determine if the detection probability meets expectations. MLE, on the other hand, uses a model to estimate the detection probability and calculates the maximum likelihood between the model and the observations. MLE can be used to estimate the optimal detection strategy, thereby improving the radar's detection probability.

[0058] Next, we will apply Constant False Alarm Rate (CAL) detection, a method for detecting signal strength. CAL can predict signal strength and detect weak signals within background noise. The principle of CAL is to average the intensity of each element in the background noise before measuring the signal strength, and calculate a threshold value based on a certain ratio. If the measured signal strength exceeds the threshold value, the target signal is considered to be present; otherwise, it is not. The advantages of CAL are that it effectively suppresses noise, improves the signal detection rate, and effectively reduces the false alarm rate. Furthermore, CAL can also be used for various signal detection applications, such as ship detection, radar detection, and audio detection.

[0059] In this embodiment, the false alarm probability for radar detection signals is:

[0060]

[0061] Detection probability is

[0062]

[0063] By ensuring the minimum value of the detection probability, it can be used as a performance indicator of the radar's sensing component. The radar's detection probability refers to the accuracy of the radar in detecting a specific target. The radar's detection probability can be used to measure its effectiveness. The advantages of a high radar detection probability include: 1. Effectively helping the radar to accurately detect targets and avoid false alarms; 2. Improving the radar's sensitivity, thus better detecting smaller targets; 3. Increasing the radar's detection range, thus better detecting farther targets; 4. Improving the radar's anti-jamming capability, thereby suppressing interference signals and reducing the false alarm rate; 5. Improving the radar's cost-effectiveness, thus saving costs. Therefore, the radar's detection probability is an important indicator for evaluating radar performance and can effectively improve the radar's detection effectiveness and cost-effectiveness.

[0064] Using the watchman's listening model, this invention can represent the watchman's received signal y. w for:

[0065]

[0066] Among them, z w The noise at the guard's location is represented, and the following conditions are met: Under H0, the watcher determines that there is no communication between the radar and the legitimate receiver user, and the received signal obeys... Under H1, the watcher determines that communication exists between the radar and the legitimate receiver user, and the received signal obeys... For the caretaker, this paper defines f(y) respectively. w |H0) and f(y w |H1) represents y under H0 and H1.w The likelihood function.

[0067] KL divergence is a measure of the difference between two probability distributions, also known as relative entropy. Symmetric KL divergence represents the degree of difference between two functions; a smaller value indicates a smaller difference, and vice versa. Symmetric KL divergence can be used to measure the difference between two probability distributions, as well as the difference between an estimated distribution and the true distribution. It can also be used to evaluate model fit and for feature selection and model selection in machine learning. The corresponding symmetric KL divergence can be obtained from this listening signal expression:

[0068]

[0069] Where D(f1||f0) and D(f0||f1) represent the values ​​from f(y) respectively. w |H1) to f(y) w KL divergence of |H0) and f(y) w |H0) to f(y) w KL divergence of |H1).

[0070] Based on the covert communication model of the radar, a covert coefficient (ω) can be used to represent the constraint. A larger covert coefficient indicates a looser covert constraint, allowing the radar to transmit signals with higher power. Conversely, a smaller covert coefficient indicates a tighter covert constraint, requiring the radar to transmit signals with lower power.

[0071]

[0072] Combining the two constraints mentioned above, and taking the radar's transmission power into account, an optimization equation can be obtained.

[0073]

[0074]

[0075] P≤P max ,

[0076] P D ≥Γ,

[0077] Where Γ is the minimum value of radar sensing performance, γ b Let be the signal-to-noise ratio at the legitimate receiver user. After obtaining this formula, we can transform it into a convex set through positive semi-definite relaxation, and then directly use a solver (such as CVX) to solve it.

[0078] Semidefinite relaxation is a constrained optimization technique that provides a new approach to solving constrained optimization problems. It transforms the original constrained optimization problem into an easier-to-solve unconstrained optimization problem, that is, it transforms the original constraints into a series of semidefinite constraints that can be relaxed infinitely. The advantages of semidefinite relaxation are: 1. It can relax constraints, making the original constrained optimization problem easier to solve. 2. It can effectively utilize the original constraints, helping to improve the accuracy of the optimization results. 3. For optimization problems with lower complexity and time requirements, it can yield better results. This optimization problem can be solved using semidefinite relaxation.

[0079] Since a semidefinite relaxation optimization method is introduced, the final solution needs to be obtained by determining the rank-one condition. If it is rank-one, the solution is directly decomposed; otherwise, Gaussian randomization is performed to obtain a high-quality rank-one solution.

[0080] In summary, the optimal beamforming method can be obtained, and by deploying this beamforming method in the radar, the optimal communication solution can be achieved.

[0081] After careful research, this paper proposes a covert communication method based on the integration of radar, communication, and sensing. By combining the communication and sensing signals transmitted by the radar, the dual objectives of communication and sensing can be achieved while resisting eavesdropping by observers. This paper also proposes using semi-definite relaxation to solve the convex optimization problem of beamforming signals, thereby maximizing the signal-to-noise ratio (SNR). In summary, the proposed radar-communication-sensing integrated covert communication method can improve both communication efficiency and security, contributing to the realization of secure and efficient communication.

[0082] Figure 2 This graph compares the simulation and numerical results of the false alarm rate and false negative rate in the example of this invention. The sum of the false negative rate and the detection probability is 1. Numerical results are derived from mathematical models and methods used to describe the characteristics of the system. Simulation results, on the other hand, are obtained by simulating the actual behavior of the system. Numerical results are more accurate but often require more computation, while simulation results are more practical but limited by the accuracy of the simulation. According to this graph, the formula derivation of the false alarm rate and detection probability in the example of this invention is consistent with the simulation results.

[0083] Figure 3This is a simulation diagram of the concealment rate with respect to different concealment coefficients under different transmit powers, representing an example of the present invention. As the transmit power increases, the signal-to-noise ratio at the legitimate receiver user increases, and the concealment rate also increases synchronously, which is consistent with reality. However, as the transmit power increases, the concealment performance gradually becomes insufficient. After reaching a certain transmit power, further increases will no longer improve the signal-to-noise ratio at the legitimate receiver user, because further increases in transmit power may lead to the information being detected by the watcher.

[0084] Figure 4 This is a simulation diagram illustrating the concealment rate of this invention under different radar antenna counts and different numbers of observer antennas. As the number of radar antennas increases, the signal-to-noise ratio at the legitimate receiver user gradually increases, and the concealment rate also increases. If the number of radar antennas is greater than the number of observer antennas, the radar can use some of its antenna capabilities to counter the observer antennas, thus allowing the remaining antennas to be fully used for transmitting information. Consequently, the signal-to-noise ratio at the legitimate receiver user will increase rapidly.

[0085] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be included in the scope of the present invention.

Claims

1. A covert communication method based on radar-communication-sensing integration, characterized in that, Includes the following steps: The transmitter radar combines sensing and communication signals into a dual-function signal, constructs a corresponding communication model based on the communication system, and describes the communication expression. Based on the communication system, a perception model is constructed, and the false alarm probability and detection probability are derived. At the same time, a listening model is constructed, the listening expression is described, and the KL divergence is derived. For radar detection signals, false alarm probability for: in, Indicates the threshold for radar detection; Detection probability for: Among them Under these circumstances, the received signal at the radar is represented by a chi-square distribution. This represents the non-central parameter in the corresponding chi-square distribution. It will increase monotonically as the non-central parameter increases; Represents the gamma function; The derivation of the KL divergence is specifically as follows: using the watcher's listening model to represent the watcher's received signal, the corresponding symmetric KL divergence is obtained as follows: in, This represents the channel coefficient at which the radar reaches the watcher. This represents the beamforming vector during radar transmission. This represents the noise variance at the guard's location. Represents the trace of a matrix; By optimizing the beamforming vector of the radar transmitter, the signal-to-noise ratio of communication is maximized, thereby improving communication performance. Specifically: in, This indicates the signal-to-noise ratio at a legitimate receiver. and Let the likelihood function represent the two cases in which the guard is listening for the signal. This represents the concealment coefficient. Indicates the maximum transmission power. This represents the minimum probability of radar detection. This indicates the transmit power of the transmitter radar. This indicates finding the square of the L2 norm. This represents the beamforming vector during radar transmission. For detection probability; The optimization is performed using a positive semidefinite relaxation method. Finally, the result is obtained by determining whether the rank of the matrix is ​​one. If the rank is one, the matrix is ​​directly decomposed; otherwise, Gaussian randomization is performed.

2. The covert communication method based on radar-communication-sensing integration according to claim 1, characterized in that, The communication model is specifically as follows: In the formula This represents the received signal at the base station. Represents a time slot. Indicates the device in the The transmitted signal in each time slot, i.e., the dual-function signal, This is the channel vector between the radar and the legitimate receiver user. This indicates the operation of conjugate transpose, and the signal conforms to a Rayleigh flat fading channel; The additive white Gaussian noise at the legitimate receiver user has a mean of 0 and a variance of . The complex Gaussian distribution, i.e. ; This indicates the signal transmitted before radar beamforming. ,in It indicates a desire for the expected value.

3. The covert communication method based on radar-communication-sensing integration according to claim 1, characterized in that, The perception model is specifically as follows: Received signals at the radar for: in, This indicates that there is no target at the destination of the radar scan. This indicates that a target exists at the destination of the radar scan; Indicates channel attenuation; and Let represent the transmit turning vector and the receive turning vector, respectively, and they are equal; This indicates the noise at the radar location. .

4. The covert communication method based on radar-communication-sensing integration according to claim 3, characterized in that, The construction of the listening model, describing the listening expression, is specifically as follows: The monitoring model of the guard represents the signal received by the guard. for: in, This represents the channel coefficient at which the radar reaches the watcher; This indicates the noise at the radar location. ;in, This indicates that the radar did not send a signal, and therefore the watcher did not receive a signal either; This indicates that the radar sent a signal, and therefore the watcher also received the signal.

5. A covert communication system based on integrated radar, communication, and sensing, characterized in that, The system is implemented using the covert communication method as described in any one of claims 1-4, including a transmitter radar, a legitimate receiver user, a target, and a watcher; the transmitter radar combines sensing signals and communication signals into a dual-function signal and transmits it to both the target and the legitimate receiver user; The watcher monitors the communication between the transmitter radar and the legitimate receiver user; by optimizing the beamforming vector at the transmitter radar, secure communication is achieved while simultaneously detecting the presence of a target.

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