Name
Abstract | ||
|---|---|---|
Frequency diverse array (FDA) is an emerging technology, the hybrid of FDA and multiple-input-multiple-output (FDA-MIMO) under monostatic scenarios has received much attention in recent years. However, little work have been done for bistatic FDA-MIMO radar. In this paper, we investigate strategies on estimating direction-of-departure (DOD), direction-of-arrival and range for bistatic FDA-MIMO radar. Our strategies have two aspects. First, nonlinear frequency increments including both subarray and random modes are employed to overcome the problem that the DOD and range parameters of FDA transmitting steering vectors are coupled. Second, in order to reduce the computational complexity associated with the 3-D spectral peak searching algorithms, estimation of signal parameters via rotational invariance technique and parallel factor algorithms with their corresponding phase ambiguity resolving methods, are proposed for subarray and random modes, respectively. Both of the two algorithms perform well while the range parameter of targets satisfy a range constraint criterion. This criterion can also be used for designing frequency increments of bistatic FDA-MIMO radar. Additionally, the Cramer-Rao bound of bistatic FDA-MIMO radar and the algorithm performance analysis consist of identifiability and complexity are derived. All the proposed methods are verified by both theoretical analysis and numerical simulations. And satisfactory results are achieved. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACCESS.2018.2816780 | IEEE ACCESS |
Keywords | Field | DocType |
Target localization,frequency diverse array (FDA),multiple-input multiple-output (MIMO) radar,ESPRIT,PARAFAC | Radar,Rotational invariance,Nonlinear system,Search algorithm,Computer science,Range constraint,Identifiability,Algorithm,Bistatic radar,Computational complexity theory,Distributed computing | Journal |
Volume | ISSN | Citations |
6 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Can Cui | 1 | 12 | 2.22 |
| Jian Xu | 2 | 224 | 55.55 |
| Ronghua Gui | 3 | 6 | 2.78 |
| Wen-Qin Wang | 4 | 368 | 45.93 |
| Wen Wu | 5 | 5 | 4.53 |