Research on electromagnetic environmental sensory based on MIMO radar and its key technologies

Zhu, Lijun; Deng, Lifei; Shan, Zebiao; Zhang, Zhen

doi:10.1504/ijsnet.2014.060737

Cited by 1 publication

(2 citation statements)

References 5 publications

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“…1,8–11 However, these methods need to search the entire solution domain; it cannot overcome the inherent shortcomings for large calculation amount. In recent years, there have been a number of spectrum search methods based on intelligent optimization algorithm, such as the genetic algorithm (GA), 12–14 the particle swarm algorithm, 12,16 cuckoo algorithm, 17 niche leapfrog algorithm, 15,18,19 etc. These algorithms do not need to search the whole solution domain, so they can greatly reduce the calculation amount.…”

Section: Introductionmentioning

confidence: 99%

“…However, because of the lack of gradient information, it is necessary to calculate the spectrum peak in a wide range and the amount of calculation cannot be further reduced. In the literature, 16 the first- and second- order derivatives of the uniform line array is analyzed, and the MUSIC spectrum search method of the line array is given. This method takes into account both the estimation accuracy and the computational complexity, and makes full use of derivative information to determine the search step, can effectively reduce the amount of calculation while ensuring the accuracy of estimation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The iterative search approach DOA estimation of monostatic L-shaped array MIMO radar

Guan

Shi

Deng

et al. 2018

Journal of Algorithms & Computational Technology

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In the DOA estimation of monostatic L-shaped array MIMO radar, Multiple Signal Classification algorithm is efficient. But the peak searching process of Multiple Signal Classification algorithm needs large amount of spectrum calculation. Focusing on the spectrum peak searching process of Multiple Signal Classification, an iterative search approach to reduce the calculation amount is proposed. The first-and second-order derivatives of Multiple Signal Classification spectrum functions are achieved and the calculation amount is analyzed. Two-dimensional Newton iteration methods are applied with multisearching threads and derivation information. The searching approach can greatly reduce the computational complexity of Multiple Signal Classification spectrum peak searching. The total calculation amount of the first and second derivatives is about 15 times of the spectrum function. However, in the two-dimensional searching, especially in the high accuracy processes, the amount of searched points can be reduced by ten hundreds times, and the computation is much lower than the common spectrum peak searching method. The simulation results show that when the search thread number reaches 100, the searching process can effectively achieve the entire spectrum peak and get the correct DOA estimation.

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