PROJECT TITLE:

Compressive sensing???based algorithm for passive bistatic ISAR with DVB-T signals

ABSTRACT:

Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. But, television broadcast-transmitted signals offer poor vary resolution for imaging purposes, as a result of they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer vary resolutions, signals composed of multiple DVB-T channels are needed. Problems arise, however, as a result of DVB-T channels are typically widely separated within the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based mostly algorithms are used to make the ISAR image. During this paper, compressive sensing theory is investigated to address this drawback because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization drawback underneath the constraint of signal sparsity, passive ISAR pictures will be obtained with strongly reduced grating lobes. Each simulation and experimental results are shown to demonstrate the validity of the proposed approach.


Did you like this research project?

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


PROJECT TITLE :Structure-Aware Bayesian Compressive Sensing for Frequency-Hopping Spectrum Estimation With Missing Observations - 2018ABSTRACT:During this Project, we tend to address the matter of spectrum estimation of multiple
PROJECT TITLE :Efficient Compressive Channel Estimation for Millimeter-Wave Large-Scale Antenna Systems - 2018ABSTRACT:Giant-scale antenna systems are thought of as a viable technology to catch up on huge path loss in millimeter-wave
PROJECT TITLE :Frequency-Domain Compressive Channel Estimation for Frequency-Selective Hybrid Millimeter Wave MIMO Systems - 2018ABSTRACT:Channel estimation is helpful in millimeter wave (mm-wave) MIMO communication systems. Channel
PROJECT TITLE :Compressive Channel Estimation and Multi-User Detection in C-RAN With Low-Complexity Methods - 2018ABSTRACT:This Project considers the channel estimation (CE) and multi-user detection (MUD) problems in cloud radio
PROJECT TITLE :Compressive Representation for Device-Free Activity Recognition with Passive RFID Signal Strength - 2018ABSTRACT:Understanding and recognizing human activities could be a basic research topic for a big selection

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

Project Enquiry