FMCW sparse array imaging and restoration for microwave gauging

[摘要] The application of imaging radar to microwave level gauging represents aprospect of increasing the reliability of target detection. The aperturesize of the used sensor determines the underlying azimuthal resolution. Inconsequence, when FMCW-based multistatic radar (FMCW: frequency modulatedcontinuous wave) is used, the number of antennas dictates this essentialproperty of an imaging system. The application of a sparse array leads to animprovement of the azimuthal resolution by keeping the number of arrayelements constant with the cost of increased side lobe level. Therefore,ambiguities occur within the imaging process. This problem can be modelledby a point spread function (PSF) which is common in image processing. Hence,an inverse system to the imaging system is needed to restore uniqueinformation of existing targets within the observed radar scenario.

In general, the process of imaging is of ill-conditioned nature andtherefore appropriate algorithms have to be applied. The present paper firstdevelops the degradation model, namely PSF, of an imaging system based on auniform linear array in time domain. As a result, range and azimuthdimensions are interdependent and the process of imaging has to bereformulated in one dimension. Matrix-based approaches can be adopted inthis way. The second part applies two computational methods to the giveninverse problem, namely quadratic and non-quadratic regularization. Notably,the second one exhibits an ability to suppress ambiguities. This can bedemonstrated with the results of both, simulations and measurements, andenables sparse array imaging to localize point targets more unambiguously.

[学科分类] 电子、光学、磁材料