A Parametric Method for Multicomponent Interference Suppression in Noise Radars


A technique for interference suppression in noise radars is proposed. The section of interference is domestically approximated by a polynomial, whose coefficients are estimated using the merchandise high-order ambiguity function (HAF), which successfully resolves the elements of multicomponent interference and improves noise rejection. The phase approximation is employed to concentrate and suppress the interference. For nonpolynomial phases, an algorithm that performs a piecewise polynomial approximation is developed. The algorithm is extended to house multicomponent interferences.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Application of Manifold Separation to Parametric Localization for Incoherently Distributed Sources - 2018ABSTRACT:By using the manifold separation technique (MST), we develop a computationally efficient nonetheless
PROJECT TITLE : Image segmentation using parametric contours With free endpoints - 2016 ABSTRACT: In this paper, we introduce a unique approach for active contours with free endpoints. A theme for image segmentation is presented
PROJECT TITLE : Theoretical analysis of penalized Maximumlikelihood patlak parametric image Reconstruction in dynamic pet for lesion detection - 2016 ABSTRACT: Detecting cancerous lesions may be a major clinical application
PROJECT TITLE : Parametric Blur Estimation for Blind Restoration of Natural Images Linear Motion and Out-of-Focus - 2014 ABSTRACT: This paper presents a replacement methodology to estimate the parameters of 2 sorts of blurs,
PROJECT TITLE :Diode-Pumped Nd:YAP Intracavity Optical Parametric Oscillator Emitting at 1603 nm: Influence of Energy-Transfer UpconversionABSTRACT:A diode-end-pumped actively $Q$-switched Nd:YAP laser at 1080 nm is originally

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry