Research On Two-dimensional Resource Adaptive Scheduling Technology Based On Cognitive Radar Networks

With the increasingly complex modern battlefield environment,the imaging tasks to be performed by radar systems are also increasing.Therefore,there is an urgent need for radar systems to complete as many imaging tasks as possible within limited resources.With the development of phased array radar technology,the development of the concept of cognitive radar,the emergence of compressed sensing theory,and the introduction of a series of sparse inverse synthetic aperture radar(ISAR)imaging algorithms,the optimal scheduling of radar resources is achieved and it becomes possible to improve the resource utilization efficiency of imaging radar systems.In order to further improve the imaging efficiency of the step-frequency radar system and the network radar system,this paper studies its adaptive resource scheduling method.In addition,in order to improve the flexibility of the system in order to better adapt to the intelligent scheduling algorithm,this paper also studies the imaging algorithm and imaging system.The main work of this article is as follows:1.The basic principles of ISAR imaging are studied,and the range-doppler imaging algorithm of the chirp radar and the ISAR imaging process of the stepped frequency system are deduced.In addition,the principle of compressive sensing and sparse reconstruction algorithm(orthogonal matching pursuit algorithm)are introduced,and the theory of compressive sensing is introduced into ISAR imaging.The sparse ISAR imaging algorithm of chirp system and stepped frequency system is studied.In addition,the influence of several typical radar system resources on ISAR imaging is analyzed.2.This paper proposes a two-dimensional resource adaptive scheduling algorithm for step-frequency ISAR imaging systems to further improve the working efficiency of radar systems.Based on the recognition of target characteristics,the algorithm first calculates the pulse resources required for the two-dimensional sparse observation of the target according to the principle of compressed sensing,and then adaptively allocates the two-dimensional pulse resources according to the two-dimensional resource scheduling model,and finally realizes multi-target alternate sparse observation imaging.The feasibility of the algorithm is verified by simulation and more imaging tasks can be performed under the condition of resource saturation compared with conventional algorithms.3.This paper proposes a time and aperture resource allocation strategy for multi-target ISAR imaging of distributed networking radars.First,based on the recognition of target features,the requirements for target resolution are determined,and the relationship between resolution and aperture resources is analyzed to establish an aperture resource allocation model under distributed networking conditions.Second,combining the sparse ISAR imaging characteristics of the target echo,the time resource is further incorporated into the resource allocation model.Thirdly,a multi-objective function model is established for the multi-target imaging situation of networking radar to consume the least resources and complete the most imaging tasks.Finally,the objective function is ranked according to the degree of importance by the method of hierarchical sequence,and a hierarchical sequence genetic algorithm is proposed to solve the optimization problem.Simulations show that the algorithm proposed in this paper is superior to traditional algorithms in terms of effective utilization of radar resources and radar system performance.4.This paper proposes a new two-dimensional imaging method based on frequency diverse ISAR.An ISAR imaging model based on a synthetic wideband signal is established,and a two-dimensional imaging of the target is completed based on an improved backward projection algorithm.On this basis,the influence of the frequency selection of the transmitted signal on the imaging quality is analyzed,and a closed form with half power resolution in the distance and azimuth directions is derived.In addition,in order to eliminate side lobes to improve imaging quality,this paper proposes a backward projection imaging algorithm based on compressed sensing combined with compressed sensing theory to obtain high-quality two-dimensional ISAR images of the target.The application of compressive sensing also provides a good guarantee for further imaging resource scheduling.Experimental results show that frequency diverse ISAR can realize two-dimensional imaging of moving multi-scattering point targets.The application of this method is of great significance for reducing the complexity and cost of the ISAR imaging system and increasing the flexibility of the system's bandwidth resources.