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Multipath Exploitation with Time Reversal Waveform Covariance Matrix for SNR Maximization
- Source :
- Remote Sensing, Vol 12, Iss 3565, p 3565 (2020)
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- Radar target detection has a wide range of applications in the military and civilian remote sensing fields; in particular, the target detection in multipath environments has attracted many scholars’ attention in recent years. The abundant multipath signals severely interfere with the detection performance and accuracy of parameter estimation of traditional algorithms. Under Gaussian white noise environments, this letter proposes an adaptive time reversal (TR) waveform covariance matrix (WCM) design method with multipath exploitation to improve the maximum signal-to-noise ratio (SNR) at the receiver in multipath environments. This equivalently improves the detection probability. The proposed two-stage algorithm firstly adapts the time-reversal echo to construct a multipath information matrix with a Hermitian structure. Secondly, the letter transforms the maximized SNR problem into semidefinite programming (SDP), which is constrained by a constant total transmit power. Consequently, the waveform covariance matrix is obtained by solving semidefinite programming. Simulation experiments verify the adaptability and effectiveness of the proposed algorithm.
- Subjects :
- multiple-input multiple-output (MIMO)
multipath exploitation
Computer science
02 engineering and technology
law.invention
symbols.namesake
0203 mechanical engineering
law
0202 electrical engineering, electronic engineering, information engineering
Waveform
signal-to-noise ratio (SNR)
Radar
Fisher information
lcsh:Science
Computer Science::Information Theory
Semidefinite programming
020301 aerospace & aeronautics
Covariance matrix
Estimation theory
020206 networking & telecommunications
White noise
waveform covariance matrix (WCM)
time reversal (TR)
symbols
General Earth and Planetary Sciences
lcsh:Q
Algorithm
Multipath propagation
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 12
- Issue :
- 3565
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....e65ebba22350254cff6e5e3aaefc3096