Research On Estimation Method Of Target Parameters In Coal Seam Near Field By Spatial Stepped Frequency Radar

With the continuous development of social economy,the energy consumption is also increasing.As one of the important social resource consumption,the safety and effectiveness of coal mining have attracted more and more attention.The timely acquisition of material information in the coal seam during the mining process can effectively improve the safety and effectiveness of mining.Ground penetrating radar(GPR)has good penetrability and fast detection speed,which is widely used in underground coal seam detection.The traditional impulse radar and single station time stepped frequency continuous wave radar have the problems of poor spatial resolution and low time utilization in the detection of heterogeneous objects in coal seam.The spatial stepped frequency radar with multiple-input and multiple-output(MIMO)can obtain larger bandwidth and aperture at the receiving end,and has higher spatial resolution.Therefore,it is of great significance to study the application of multi-input and multi-output spatial stepped frequency radar to heterogeneous body detection in coal seam media.In this paper,the far-field signal model of spatial stepped frequency radar is studied firstly.By using the orthogonality of the transmitted signal,the transmitted signals of each frequency point are separated by matching separation at the receiving end,the receiving signal model is established.Then,based on the coal seam medium,the position relationship between the heterogeneous body and the array is calculated according to the geometry of the near-field model,and the near-field equivalent received signal model with joint range and angle is obtained.Furthermore,to solve the problem of low estimation accuracy of coal seam heterogeneous bodies in the case of few snapshots and low signal-to-noise ratio,a range-angle two-dimensional power spectrum estimation method based on 2D-lq-SAMV sparse recovery algorithm is proposed.The simulation results show that the proposed 2D-lq-SAMV algorithm can accurately estimate the range-angle parameters of the target.Compared with 2D-MUSIC,NF-IAA and 2D-SAMV,the proposed method has higher estimation accuracy in the case of less snapshots and low signal-to-noise ratio.Finally,in view of the problem that the estimation performance is degraded when there are adjacent strong and weak heterogeneous bodies in coal seam media,the 2D-lq-SAMV-CRELAX joint algorithm is proposed to realize the joint estimation of two-dimensional parameters of adjacent strong and weak heterogeneous bodies.Simulation results show that,compared with 2D-RELAX algorithm,the proposed 2D-lq-SAMV-CRELAX algorithm can effectively improve the parameter estimation performance of adjacent strong and weak heterogeneous bodies,and better improve the parameter estimation accuracy of weak targets.