A fusion algorithm for cooperative reconnaissance based on the correlation of sparse representation
| Autor: | Yuanrong Tian, Dongqing Zhou, Zhipeng Wang, Yipeng Zhou, Xing Wang |
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| Rok vydání: | 2016 |
| Předmět: |
Correlation
Signal processing Fusion law Computer science 0202 electrical engineering electronic engineering information engineering 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology Sparse approximation Radar Algorithm law.invention |
| Zdroj: | 2016 IEEE 13th International Conference on Signal Processing (ICSP). |
| DOI: | 10.1109/icsp.2016.7878065 |
| Popis: | Information fusion is an important step in cooperative reconnaissance signal processing, which can be divided into three types: data-level, feature-level and decision-level fusion. Data-level fusion has the advantage of information completeness but the large data volume makes it hard to apply practically. Based on the sparse representation of intercepted signal and the correlations between signals, a data-level fusion algorithm is proposed. In the algorithm, the intercepted signal is expressed in sparse representation and compressed for communication. Then fuse the sparse coefficients based on the correlations between them. The experiments indicate that the algorithm can reduce the amount of data effectively with the same information and compared with the existing sparse representation fusion algorithm based on activeness of atom, the algorithm can reach better fusion effect. |
| Databáze: | OpenAIRE |
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