Neural network based detection scheme for slow fluctuating radar targets in low Pfa conditions

Title:

Neural network based detection scheme for slow fluctuating radar targets in low Pfa conditions

Creator:

Jarabo Amores, M. P., Rosa Zurera, M., Lopez Ferreras, F., and Lpez Espi, P.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:fe41699c-7323-44ca-86a8-a109a8b9f667
uuid:fe41699c-7323-44ca-86a8-a109a8b9f667

Subject:

neural network, radar, detection, PCA, and time-frequency analysis

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Slow fluctuating radar targets have shown to be very difficult to classify by means of neural networks. This paper deals with the application of time-frequency decompositions for improving the performance of neural networks for this kind of targets. Several topics, such as dimensionality reduction of the time-frequency representations and the optimum value of SNR for training are discussed. The proposed detector is compared with a single neural network for radar detection, showing that he performance is improved for slow fluctuating radar targets, especially for low values of the probability of false alarm.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2001 Volume:11 | Number:3

Harvested from:

CDK

Metadata only:

false