CN111273299B - Underwater distributed suppressive interference arrangement method for networking sonar - Google Patents
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Abstract
The invention provides an underwater distributed suppressive interference arrangement method for networking sonar, which takes CRB estimated by a countermeasure networking sonar system on a ship parameter as a measurement index of an interference effect, takes the CRB estimated by the maximized countermeasure sonar system parameter as an optimization function, and provides a calculation method of an optimal distribution position of a distributed interference source. Compared with the traditional interference arrangement strategy, the strategy has the advantages that under the effective interference resources, the lower limit of the parameter estimation error of the warship by the anti-party sonar system is larger, the detection and tracking performance of the warship is weaker, and the purpose of avoiding the tracking or attack of the anti-party networking sonar system on the warship is achieved.
Description
Technical Field
The invention belongs to the technical field of underwater acoustic countermeasure, and relates to an interference method for underwater networking sonar.
Background
Underwater countermeasure technology typically includes underwater countermeasures whose primary task is to probe and track the anti-countermeasures platform and anti-countermeasures whose primary task is to avoid identification by their probing. With the development of underwater acoustic technology, underwater target detection technology is not limited to single sonar equipment, and networking sonar detection systems are receiving more and more attention from various countries. Compared with the traditional single sonar detection device, the networking sonar detection system can obtain more information except the target direction, such as target distance and the like, so that the aims of early warning, tracking and even identifying the target can be achieved. As an anti-countermeasure, in order to effectively resist an underwater networking sonar detection system and avoid the local platform (such as a submarine, a surface ship and the like) from being discovered by an anti-sonar, a noise interference device is required to be used for transmitting high-power interference noise to reduce the receiving signal-to-noise ratio of the anti-sonar, so that the detection capability is reduced.
Currently, the research on underwater acoustic interference technology in the field of underwater acoustic countermeasure is mainly focused on the countermeasure of single sonar detection equipment, the interference effect of a noise interference suppressor on single passive sonar is researched by Down-builder in the document "influence and simulation analysis of noise interference on passive sonar systems" (Acoustic technology, 2015,34 (5): 365-368.), and the optimum placement position of the noise interference suppressor on single passive sonar is researched by Yangery in the document "optimum placement position and depth research of noise interference suppressor" (war institute, 2014,35 (4): 484-488.). Most of the existing researches adopt a single interference unit to resist the countermeasure mode of single sonar equipment, however, for a networking sonar system, the single noise interference unit obviously cannot effectively interfere all detection sonars, so that a distributed interference system consisting of a plurality of interference units is required to resist. Currently, the distributed interference technology is mainly applied in The field of Radar, and XF Song et al studied The interference power distribution strategy of The distributed interference countermeasure MIMO Radar system from The perspective of game theory in The document "The MIMO Radar and Jammer gams" (IEEE Transactions on Signal Processing,2011,60 (2): 687-699), but did not study The placement position of The distributed interference source. When distributed interference is used, the interference effect of the distribution position of the interference unit on the whole system is greatly influenced, so that an optimal arrangement strategy for the distributed interference countering networking sonar system is urgently needed.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an underwater distributed suppressive interference strategy, which can design the optimal distribution position of an interference device according to the current available interference device resource, so that the parameter estimation performance of an anti-party networking sonar system on the operation platform (a submarine or a surface ship and the like, hereinafter referred to as a ship) is weakest, and the aim of avoiding the tracking or the attack of the anti-party networking sonar system on the ship is fulfilled.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps:
s1, determining radiation signal S of ship m (t) and the distance between the ship and each sonar matrix in the anti-party networking sonar system
L =1,2, \8230, L is the L receiving matrix in the anti-square networking sonar, M =1,2, \8230, M is the M local combat platform;
s2, determining available interference resources of the ship, including the number K of available interferors and interference emission noise n of the kth interferometer k (t) interference distance of kth interference unit to the l receiving matrix
Wherein K =1,2, \ 8230, K denotes the kth interferer, and the available K interferers are emitted by M vessel platforms;
s3, calculatingEach sonar basic array receiving signal
In the formula, t =1,2, \ 8230, N is the number of signal sampling points;
receiving the matrix of noisy signals, P, for the ith matrix l Representing the array element number contained in the first array;
is a radiation signal matrix of the ship,
e l (t) indicating isotropic marine environmental noise received by the ith array, wherein the marine environmental noise received by each array is independent; matrix of
Is the ship signal direction vector theta containing attenuation coefficient in the first sonar basic array T For M ship platforms relative to the angle matrix of the enemy sonar receiving matrix, namely theta T ＝[θ T1 ,θ T2 ,…,θ TM ]；A l (θ T ) Is represented as follows:
wherein,
the propagation loss coefficient from the mth target to the lth sonar basic array is obtained;
is at theta Tm The direction vector of the m-th target signal in the direction to the l-th array,
wherein Δ l Is the array element spacing of the first matrix, and lambda represents the wave of the acoustic signal in the sea waterLength;
is a matrix of the interference noise which is,
assuming that the noise power of the interference source reaching each array element on the same sonar basic array is the same, the matrix B l ∈C 1×K For the interference noise direction vector containing the attenuation coefficient,
wherein,
is at theta Jk Propagation loss from the kth interference source to the ith array in the direction;
namely the interference noise power received by the sonar basic array; then the total power of the interference noise and the environmental noise received by the ith anti-sonar basic array
Wherein σ k Transmitting noise power, σ, for the k-th interferer 0 Is the marine environmental noise power;
s4, according to a receiving matrix signal model in the presence of distributed interference in the S3, the networking sonar system estimates the ship target angle by using the CRB
In the formula,
G＝H -1
s5, the CRB obtained by calculation in the step S4 is an M multiplied by M matrix, and diagonal elements of the matrix are respectively
The sensor network estimates the variance C of the angle of each target m I.e. by
By maximizing the weighted average CRB of the estimation of each target angle, the optimal distribution angle of the interference source can be obtained
Wherein λ is 1 ,…,λ M Is a regularization factor;
s6, solving the optimal layout angle of the kth interference source into
The optimal deployment position
Wherein r is k The distance of the kth interference source from the origin of coordinates.
The CRB formula in the step S4 adopts CRB estimated by networking sonar on other parameters of the target, and the CRB is taken as a target function of the optimization model in the step S5 and comprises the distance or the speed of the networking sonar on the target.
Step S5, selecting ship radiation noise power sigma sm As a criterion, the regularization factor of the mth ship target
And S6, solving the optimal distribution angle of the interference source by adopting a heuristic algorithm, wherein the optimal distribution angle comprises a particle swarm optimization algorithm, a genetic algorithm and a simulated annealing algorithm.
The beneficial effects of the invention are: CRB estimated by the countermeasure networking sonar system on the ship parameter is used as a measurement index of the interference effect, and CRB estimated by the maximized countermeasure sonar system parameter is used as an optimization function, so that a calculation method of the optimal distribution position of the distributed interference source is provided. Compared with the traditional interference arrangement strategy, the strategy has the advantages that under the effective interference resources, the lower limit of the parameter estimation error of the warship by the anti-sonar system is larger, and the detection and tracking performance of the warship is weaker.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a scene model of a distributed suppressive interference-countering networking sonar system;
FIG. 3 is a diagram of the estimation of anti-party networking sonar parameters CRB when different deployment strategies are employed in example one;
fig. 4 shows an optimal placement position of a distributed interference source under a plurality of warships in the second example;
fig. 5 shows the estimation CRB of the anti-party networking sonar parameters when different deployment strategies are adopted in example two.
Detailed Description
The method of the invention determines the receiving signal of the anti-party networking sonar system through the known warship signal and the distributed interference transmitting noise, calculates the CRB of the anti-party networking sonar system for estimating the warship parameters according to the obtained anti-party sonar array receiving signal model, and then obtains the optimal placement position of the distributed interference source through maximizing the CRB, thereby realizing the optimal interference effect on the anti-party networking sonar system.
The technical scheme of the invention comprises the following steps:
s1, determining an underwater battlefield model:
the distributed interference effect is closely related to parameters of a ship (Target, marked as T) and a counterparty networking sonar system (Receiver, marked as R), so that the radiation signal s of the ship needs to be determined firstly m (t) and the distance between the ship and each sonar matrix in the anti-party networking sonar system
L =1,2, \8230, L is the L-th receiving matrix in anti-square networking sonar, M =1,2, \8230, and M is the M-th local combat platform.
S2, determining available interference resources of the ship:
in an underwater battlefield, a ship determines an interference strategy according to carried interference device resources, so that available interference resources including the number K of available interference devices and interference emission noise n need to be determined according to carried interference devices (Jammer, marked as J) of the ship k (t) and interference distance
Where K =1,2, \8230, K denotes the kth interferer. The available K interferers are sent out by M warship platforms, the transmission interference noise power and the interference distance of each interferer are determined by parameters of the interferers, and after the interferers run to the designated position, the distributed interference system acts on the anti-party detection sonar system.
S3, calculating each sonar array receiving signal:
the ith countermeasure sonar basic array received signal model can be expressed as:
in the formula, t =1,2, \8230, N is the number of signal sampling points;
receiving the matrix of noisy signals, P, for the ith matrix l Representing the array element number contained in the first array;
is a matrix of the radiation signals of the ship,
e l (t) indicating isotropic marine environmental noise received by the ith array, wherein the marine environmental noise received by each array is independent; matrix array
Is the signal direction vector theta of the ship containing attenuation coefficient in the ith matrix T For M ship platforms relative to the angle matrix of the enemy sonar receiving matrix, namely theta T ＝[θ T1 ,θ T2 ,…,θ TM ]。A l (θ T ) Is represented as follows:
wherein,
propagation loss coefficient and distance for the mth target to the lth array
In this regard (under spherical propagation conditions,
is at theta Tm The directional vector from the m-th target signal to the l-th array in the direction under the assumption of a Uniform Linear Array (ULA) is as follows:
wherein Δ l The array element spacing of the first matrix, λ represents the wavelength of the acoustic signal in the sea water, usually Δ l ＝λ/2。
wherein,
is at theta Jk Propagation loss from the k-th interference source to the l-th array in the direction, and distance
It is related.
I.e. the interference noise power received by the sonar array, depends on various parameters (position distribution, interference power, etc.) of the distributed interference system, and when the optimal distributed interference parameters are selected,
the maximum can be reached, so that the ship radiation signal received by the submerged sonar can be reached
The detection performance of sonar on the ship is reduced.
Then the total power of the interference noise and the environmental noise received by the ith anti-sonar basic array is:
wherein σ k Transmitting noise power, σ, for the k-th interferer 0 Is the power of the marine environmental noise.
S4, calculating a Clarithromol boundary of the parameter estimation of the warship by the countermeasure networking sonar:
the Cramer-Rao Bound (CRB) represents the lower error limit that a receiver system can estimate a target parameter in various signal processing manners, and is usually used as a measure of the performance of the receiver, and the higher the CRB of the receiver, the worse the detection performance is. The CRB is used as a measurement index of distributed interference performance, the CRB of the receiver is only related to distributed interference parameters under the condition that target parameters are not changed, when a reasonable distributed interference arrangement strategy is adopted, the optimal interference effect can be achieved, at the moment, the CRB of the receiver reaches the highest level, and the interference effect of the distributed interference on parameter estimation performance of an adversary receiving system is strongest.
According to a receiving matrix signal model in the presence of distributed interference in the S3, the CRB of the networking sonar system for estimating the ship target angle is as follows:
in the formula,
G＝H -1
s5, establishing a mathematical model of a distributed interference optimal arrangement strategy:
the method takes the angle estimation CRB of the warship of the anti-party networking sonar system as a measurement index of the interference effect, and takes the maximum anti-party sonar system CRB as an optimization function. When the ship signal and the environmental noise are given, the CRB of the anti-sonar system only depends on the distributed interference parameters, and the number K of the interferers and the interference emission noise n are already determined in step S2 k (t) and interference distance
Therefore, the parameter estimation performance of the sonar against the side only has the distribution angle of each interference source
It is relevant. By solving the optimization problem based on the CRB maximization, the optimal distribution angle of the distributed interference source can be obtained.
The CRB calculated in step S4 is an M × M matrix, and diagonal elements of the matrix are angle estimation variances C of the sensor network for each target respectively m Namely:
then, by maximizing the weighted average CRB of the estimation of each target angle, the optimal deployment angle of the interference source can be obtained
Wherein λ is 1 ,…,λ M The regularization factor is determined according to the importance degree of the corresponding ship target, the importance degree of each ship target is different under different judgment standards, and the regularization factor can be determined according to the requirements of actual combat missions. For example, if the power sigma of the radiated noise of the ship is selected sm As a criterion for evaluation, then the regularization factor of the mth vessel target can be expressed as
S6, solving the optimal distribution position of the distributed interference source:
the model is a complex and non-convex optimization problem, so that a heuristic algorithm can be adopted for solving, such as a particle swarm optimization algorithm, a genetic algorithm, a simulated annealing algorithm and the like. The optimal deployment angle of the kth interference source is obtained by solving
Then the optimal deployment position is:
wherein r is k The distance of the kth interference source from the origin of coordinates.
The CRB of the warship target angle estimation of the anti-party networking sonar system is used as an index for measuring the distributed interference effect, when each interference source adopts an optimal distribution strategy, the CRB of the anti-party networking sonar on the warship target angle estimation can be maximized, namely the lower limit of the angle estimation error of the anti-party on the warship target is maximized, the detection capability is weakest, and therefore the distributed interference system can achieve the best interference effect. Usually, the parameter estimation of the networking sonar on the target also includes estimation of distance, speed and the like, so the CRB formula in step S4 can also be a CRB of the networking sonar on other parameter estimation of the target, and the CRB formula is used as an objective function of the optimization model in step S5, and the optimization model and the calculation method are the same as those in steps S5 and S6.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the embodiments described are merely exemplary of some rather than all embodiments of the invention and that all other embodiments that may be derived by one of ordinary skill in the art based on the embodiments herein without undue experimentation will be within the scope of the present invention.
Example one
An underwater battlefield model is first determined, and the battlefield layout is shown in fig. 2. Assuming that the scene contains a single local combat platform, the radiation signal is white Gaussian noise with the power of 110dB at the (0, 0) point; the anti-square networking sonar system consists of 3 passive sonar basic arrays, all of which are 8-element uniform linear arrays and are respectively positioned in the directions of 10 degrees, 30 degrees and 50 degrees of the ship, and the following two conditions are respectively analyzed:
in the first case, the distance from each array to the ship is fixed to [2600m 2500m 2600m ], so that the 30-degree array has the strongest detection performance in the networking sonar;
in the second case, the distance from each array to the ship is fixed to be [2500m, 2500m ], and then the receiving performance of each array in the networking sonar is the same.
Suppose that the ship carries 3 available interferers, the emission noise is white gaussian noise with the power of 110dB, and the interference source is 2000m away from the ship.
After defining the underwater battlefield model and the available interference resources, modeling is carried out on the sonar array received signals of the countermeasure networking according to the step S3, and a distributed interference optimal arrangement strategy optimization model based on CRB maximization is established according to the step S4. Because the model is a complex and non-convex optimization problem, particle swarm optimization is adopted to solve in the simulation example of the invention.
For different environmental noise variance σ 0 The optimal angle of the interference source is calculated, and the result is recorded in table 1. In the second case, the variance σ is adjusted for different environmental noises 0 The resulting CRB is marked in fig. 3 by using a centralized placement strategy, a random placement strategy, a uniform placement strategy, and an optimal placement strategy, respectively.
Table 1 optimal layout angle of distributed interference in different environmental noises under single-object scene
In case one of example one, assume that the array in the 30 ° direction is closest to the target and therefore has the strongest detection performance. As can be seen from Table 1, when the ambient noise variance σ 0 When smaller, the optimal deployment angle of the interference source is close to the array angle, whereas when the ambient noise variance σ is small 0 When the distribution angle is gradually increased, the optimal distribution angle of the interference source tends to be concentrated; and the result obtained from the second condition shows that the optimal deployment angle of each interference source is concentrated on the array in the middle position of the networking sonar when the environmental variance is large no matter whether the array detection performance is the same or not.
As can be seen from fig. 3, the CRB of the networking sonar obtained by the optimization strategy proposed by the present invention for target angle estimation is higher than that of the other three strategies, and particularly in the case of weak environmental noise, the CRBs obtained by the four interference methods are not very different as the environmental noise is increased, because the noise signal acting on the receiver is mainly the environmental noise. Therefore, the distributed interference optimal placement strategy provided by the invention has greater advantages under the condition of weak environmental noise.
Example two
Suppose that the battlefield model of example two contains 3 local operation platforms which radiate informationThe same number, white Gaussian noise with power of 110dB, are distributed in [0,0 ] respectively]、[2000,0]、[0,1000](coordinate unit is m), if the importance of each platform is the same, then there is λ in step S5 1 ＝λ 2 ＝λ 3 =1/3; the anti-square networking sonar system consists of 3 passive sonar basic arrays, wherein the 3 passive sonar basic arrays are 8-element uniform linear arrays and are respectively positioned in 10 degrees, 30 degrees and 50 degrees of the ship, and the distance from each array to a coordinate origin (the ship 1) is fixed to be [2500m 2500m 2500m 0m]。
The ship is assumed to carry 6 interferers with the transmission noise power of 110dB, and the distance between an interference source and a coordinate origin (ship 1) is 2000m. And similarly, establishing a distributed interference optimization step strategy optimization model through the step S3 and the step S4, and solving by adopting a particle swarm optimization algorithm.
Firstly, the noise level sigma of the marine environment 0 The interference source optimum angle calculation at =30dB, the result is marked in fig. 4. Then respectively at σ 0 In the case of = 30-70 dB, four different interference strategies are used, and the results are marked in fig. 5. As can be seen from fig. 4, the distributed interference sources still tend to be distributed according to the array angle in the case of multiple targets, because the distributed interference is usually in a close-range interference manner, and therefore the optimal interference distribution angle is greatly related to the networking sonar structure. Fig. 5 shows that under different environmental noises, networking sonar angle estimation CRBs obtained by respectively adopting a centralized deployment strategy, a random deployment strategy, a uniform deployment strategy and an optimal deployment strategy have the best interference effect in a multi-objective complex scene.
Claims (4)
1. An underwater distributed suppressive jamming deployment method for networked sonar, characterized by comprising the steps of:
s1, determining radiation signal S of ship m (t) and the distance between the ship and each sonar matrix in the anti-party networking sonar system
Wherein L =1,2, \ 8230and L is antagonismThe first receiving matrix in the square networking sonar, M =1,2, \ 8230, wherein M is the mth operation platform;
s2, determining available interference resources of the ship, including the number K of available interferors and interference emission noise n of the kth interferometer k (t) interference distance of kth interference unit to the l receiving matrix
Wherein K =1,2, \ 8230, K denotes the kth interferer, and the available K interferers are emitted by M vessel platforms;
s3, calculating each sonar basic array receiving signal
In the formula, t =1,2, \8230, N is the number of signal sampling points;
receiving the matrix of noisy signals, P, for the ith matrix l Expressing the array element number contained in the first array;
is a radiation signal matrix of the ship,
e l (t) isotropic marine environmental noise received by the ith array is represented, and the marine environmental noise received by each array is independent; matrix array
Is the ship signal direction vector theta containing attenuation coefficient in the first sonar basic array T For M ship platforms relative to the angle matrix of the enemy sonar receiving matrix, i.e. theta T ＝[θ T1 ,θ T2 ,…,θ TM ]；A l (θ T ) Is represented as follows:
wherein,
the propagation loss coefficient from the mth target to the lth sonar basic array is obtained;
is at theta Tm The direction vector of the m-th target signal in the direction to the l-th array,
wherein Δ l The array element spacing of the first matrix is shown, and lambda represents the wavelength of the acoustic signal in the seawater;
is a matrix of the interference noise which is,
assuming that the noise power of the interference source reaching each array element on the same sonar basic array is the same, the matrix B l ∈C 1×K For the interference noise direction vector containing the attenuation coefficient,
wherein,
is at theta Jk Propagation loss from the kth interference source to the ith array in the direction;
namely the interference noise power received by the sonar array; then the total power of the interference noise and the environmental noise received by the ith anti-sonar basic array
Wherein σ k For the kth interference sourcePower of transmitted noise, σ 0 Is the marine environmental noise power;
s4, according to a receiving matrix signal model in the presence of distributed interference in the S3, the networking sonar system estimates the angle of the ship target CRB
In the formula,
G＝H -1
s5, the CRB obtained by calculation in the step S4 is an M multiplied by M matrix, and diagonal elements of the matrix are angle estimation variances C of the countermeasure networking sonar system on each target respectively m I.e. by
By maximizing the weighted average CRB of the estimation of each target angle, the optimal distribution angle of the interference source can be obtained
Wherein λ is 1 ,…,λ M Is a regularization factor;
s6, solving the optimal layout angle of the kth interference source into
The optimal deployment position
Wherein r is k The distance of the kth interference source from the origin of coordinates.
2. The underwater distributed suppressive disturbance deployment method for networked sonar according to claim 1, wherein: the CRB formula in the step S4 adopts the CRB estimated by the networking sonar on other parameters of the target, and the CRB is used as a target function of the optimization model in the step S5 and comprises the distance or the speed of the networking sonar on the target.
3. The underwater distributed suppressive jamming deployment method for networked sonar of claim 1, characterized by: step S5, selecting ship radiation noise power sigma sm As a criterion for evaluation, the regularization factor of the mth ship target
4. The underwater distributed suppressive disturbance deployment method for networked sonar according to claim 1, wherein: and S6, solving the optimal distribution angle of the interference source by adopting a heuristic algorithm, wherein the heuristic algorithm comprises a particle swarm optimization algorithm, a genetic algorithm and a simulated annealing algorithm.
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