Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage

This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.

Optimization method of linear barrier coverage deployment for multistatic radar

To address the problem of building linear barrier coverage with the location restriction, an optimization method for deploying multistatic radars is proposed, where the location restriction splits the deployment line into two segments. By proving the characteristics of deployment patterns, an optimal deployment sequence consisting of multiple deployment patterns is proposed and exploited to cover each segment. The types and numbers of deployment patterns are determined by an algorithm that combines the integer linear programming(ILP)and exhaustive method(EM). In addition, to reduce the computation amount, a formula is introduced to calculate the upper threshold of receivers’ number in a deployment pattern. Furthermore, since the objective function is non-convex and non-analytic, the overall model is divided into two layers concerning two suboptimization problems. Subsequently, another algorithm that integrates the segments and layers is proposed to determine the deployment parameters, such as the minimum cost, parameters of the optimal deployment sequence, and the location of the split point. Simulation results demonstrate that the proposed method can effectively determine the optimal deployment parameters under the location restriction.

Deceptive jamming suppression in multistatic radar based on coherent clustering

This paper proposes a suppression method of the deceptive false target(FT) produced by digital radio frequency memory(DRFM) in a multistatic radar system. The simulated deceptive false targets from DRFM cannot be easily discriminated and suppressed with traditional radar systems. Therefore, multistatic radar has attracted considerable interest as it provides improved performance against deception jamming due to several separated receivers. This paper first investigates the received signal model in the presence of multiple false targets in all receivers of the multistatic radar. Then, obtain the propagation time delays of the false targets based on the cross-correlation test of the received signals in different receivers. In doing so, local-density-based spatial clustering of applications with noise(LDBSCAN) is proposed to discriminate the FTs from the physical targets(PTs) after compensating the FTs time delays, where the FTs are approximately coincident with one position, while PTs possess small dispersion.Numerical simulations are carried out to demonstrate the feasibility and validness of the proposed method.

Moving target localization for multistatic passive radar using delay, Doppler and Doppler rate measurements

Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended cross ambiguity function, offers an opportunity to further enhance the localization accuracy. This paper considers using the measurement Doppler rate in addition to measurements of time delay and Doppler shift to locate a moving target. A closed-form solution is developed to accurately and efficiently estimate the target position and velocity.The proposed solution establishes a pseudolinear set of equations by introducing some additional variables, imposes weighted least squares formulation to yield a rough estimate, and utilizes the function relation among the target location parameters and additional variables to improve the estimation accuracy. Theoretical covariance and Cramer-Rao lower bound(CRLB) are derived and compared, analytically indicating that the proposed solution attains the CRLB. Numerical simulations corroborate this analysis and demonstrate that the proposed solution outperforms existing methods.

Data fusion of target characteristic in multistatic passive radar

Radar cross section(RCS)is an important attribute of radar targets and has been widely used in automatic target recognition(ATR).In a passive radar,only the RCS multiplied by a coefficient is available due to the unknown transmitting parameters.For different transmitter-receiver(bistatic)pairs,the coefficients are different.Thus,the recovered RCS in different transmitter-receiver(bistatic)pairs cannot be fused for further use.In this paper,we propose a quantity named quasi-echo-power(QEP)as well as a method for eliminating differences of this quantity among different transmitter-receiver(bistatic)pairs.The QEP is defined as the target echo power after being compensated for distance and pattern propagation factor.The proposed method estimates the station difference coefficients(SDCs)of transmitter-receiver(bistatic)pairs relative to the reference transmitter-receiver(bistatic)pair first.Then,it compensates the QEP and gets the compensated QEP.The compensated QEP possesses a linear relationship with the target RCS.Statistical analyses on the simulated and real-life QEP data show that the proposed method can effectively estimate the SDC between different stations,and the compensated QEP from different receiving stations has the same distribution characteristics for the same target.

ANALYSIS OF TARGET TRACKING BASED ON RANGE DIFFERENCE MEASUREMENT OF MULTISTATIC RADAR SYSTEM

An analysis is presented for target tracking with short range multistatic radar system in this paper. The velocity vector is introduced into the model to depict target motion more precisely. The system measurement equation is such constructed on the basis of range difference that make the tracking model independent of the transmitter position. Therefore the algorithm is very much suitable for the case that the transmitter is not fixed. Simulation results show that the algorithm has the advantages of fast tracking and small steady tracking errors, and can be used for tracking target in short range with multistatic radar system.

A NEW METHOD FOR DETERMINING THE LOCATION AND LENGTH OF A THIN CYLINDRICAL TARGET WITH RANGE DIFFERENCE OF A MULTISTATIC RADAR SYSTEM

This paper describes a short range target location system based on the range difference information of a T-R4 multistatic radar system with FMCW signal. A new method is proposed to determine the location and length of a thin cylindrical target making use of the high resolution of wide band FMCW signal and the spectrum characteristics of the target echo. Formulae are derived for target location and its length estimation being independent of the transmitter position. System performances are simulated with the proposed algorithm and the results are given for various situations.

Detection, Identification and Tracking of Flying Objects in Three Dimensions Using Multistatic Radars

Multistatic radar systems can be used in many applications such as homeland security, anti-air defense, anti-missile defense, ship’s navigation and traffic control systems. Multistatic radars, which are capable of detecting and tracking flying objects in three-dimension coordinate systems, are simulated in this paper. The location and velocity of flying objects as well as their radar cross sections are computed. The object’s path is also estimated by tracking the object.

Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar

The resolution of the multistatic passive radar imaging system(MPRIS)is poor due to the narrow bandwidth of the signal transmitted by illuminators of opportunity.Moreover,the inaccuracies caused by the inaccurate tracking system or the error position measurement of illuminators or receivers can deteriorate the quality of an image.To improve the performance of an MPRIS,an imaging method based on the tomographic imaging principle is presented.Then the compressed sensing technique is extended to the MPRIS to realize high-resolution imaging.Furthermore,a phase correction technique is developed for compensating for phase errors in an MPRIS.Phase errors can be estimated by iteratively solving an equation that is derived by minimizing the mean recovery error of the reconstructed image based on the principle of fixed-point iteration technique.The technique is nonparametric and can be used to estimate phase errors of any form.The effectiveness and convergence of the technique are confirmed by numerical simulations.

ANALYSIS OF THE RETURNED SIGNAL MODEL IN BISTATIC RADAR SYSTEMS

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Joint waveform selection and power allocation algorithm in manned/unmanned aerial vehicle hybrid swarm based on chance-constraint programming

In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. Accordingly,the low probability of intercept(LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section(RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation(ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation,the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound(BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelli gent algorithms, in which the stochastic simulation is integrated into the genetic algorithm(GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.