A Novel Neural Network Based Direction Of Arrival Estimation Algorithm
The basics of Neural Network Based Direction of Arrival Estimation, details of Novel Neural Network Algorithm
Versandkostenfrei!
Versandfertig in 6-10 Tagen
38,99 €
inkl. MwSt.
PAYBACK Punkte
19 °P sammeln!
Direction of Arrival Estimation (DoA) is one of the major problems for many applications such as radar, navigation, mobile communications, electronic warfare systems, sonar and seismology. In the previous decade some powerfull and high-resolution methods for DoA estimation such as MUSIC and ESPRIT had already been developed. However, these conventional methods were having some drawbacks such as the number of arriving sources must be less than the number of antenna array elements and a accuracy degradation of DoA estimation under low SNR. Therefore they were not able to meet real-time requireme...
Direction of Arrival Estimation (DoA) is one of the major problems for many applications such as radar, navigation, mobile communications, electronic warfare systems, sonar and seismology. In the previous decade some powerfull and high-resolution methods for DoA estimation such as MUSIC and ESPRIT had already been developed. However, these conventional methods were having some drawbacks such as the number of arriving sources must be less than the number of antenna array elements and a accuracy degradation of DoA estimation under low SNR. Therefore they were not able to meet real-time requirements. Rapid growth in wireless communication accelerated the demand for DoA estimation. NN based DoA estimation algorithms have been developed to overcome the drawbacks of conventional methods and respond the demand. This book provides an overview on neural network DoA algorithms and proposes a novel algorithm. The potential applications of the proposed algorithm are discussed and consequences of simulations are provided. This book is inducing a useful, accurate and efficient algorithm for anyone who is interested in direction finding.
Andere Kunden interessierten sich für
