استفاده از روش حسگري فشرده جهت بهبود كارآيي رادارهاي چند ورودي- چند خروجي

چكيده انگليسي :

Compressive sensing for performance improvement in MIMO Radars Azra Abtahi Fahliani Azra abtahi@ec iut ac ir Date of Submission 2013 09 16 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Seyed Mahmood Modarres Hashemi modarres@cc iut ac ir Abstract Multiple input multiple output MIMO radar is a radar that consists of multiple transmitters and multiple receivers and in which all the receivers send the received signal to a common processing center for simultaneous process This radar according to its higher freedom degree in comparison with single input single output SISO radar has superior resolution higher accuracy in detection and estimation and more flexibility in beamforming MIMO radar systems are divided into two groups collocated MIMO radars and MIMO radars with widely separated antennas Important subjects in the context of MIMO radar are detection estimation and optimal transmitted waveform design There are several parameter estimation methods in collocated MIMO radars but in MIMO radars with widely separated antennas most of the time matched filters method is used Because of the existence of multiple receivers in MIMO radar systems if we be able to reduce the sampling rate and remove the need of high rate analog to digital converters the cost of receivers can be reduced Sometimes the problem is not even the cost The problem is unaccessible high sampling rate This reduction in sampling rate can be achieved by using compressive sensing CS Furthermore using CS can improve the performance of these radars in detection and estimation and also reduce the complexity of receivers and common processing center in comparison with other methods such as matched filters method CS is a new paradigm in signal processing that allows us to reconstruct spark signals accurately and even exactly from a number of samples which is much smaller than what is necessary according to Shannon Nyquist sampling theory For block sparse signals it is better to use block CS methods received signal modeling simplification all targets and antennas are considered to be located in a plane In this thesis we extend this modeling to the three dimensional case CS based MIMO radars can be improved by different methods like optimal design of measurement matrix optimal design of transmitted waveforms reducting the distance of points in estimation grids and optimal design of antenna placements The received signal in MIMO radar with widely separated antennas is block sparse in a basis So we can use block CS methods in this type of MIMO radars and it is shown that the performance will be improved In this thesis two methods for the performance improvement of block CS based MIMO radar with widely separated antennas are proposed These methods are used for reducting a measure that is named block coherence The first proposed method and the second proposed method are respectively based on optimal measurement matrix design and optimal transmitted energy allocation Simulation results show an increase in the accuracy Keywords Compressive sensing multiple input multiple output MIMO radar optimal measurement matrix design optimal transmitted energy allocation PDF created with pdfFactory trial version www pdffactory com

ابطحي فهلياني، عذري

استفاده از روش حسگري فشرده جهت بهبود كارآيي رادارهاي چند ورودي- چند خروجي

رادار MIMo , طراحي ماتريس اندازه گيري بهينه , تخصيص انرژي بهينه