scholarly journals Clutter Suppression Method for Off-Grid Effects Mitigation in Airborne Passive Radars with Contaminated Reference Signals

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6339
Author(s):  
Yaqi Deng ◽  
Wenguo Li ◽  
Saiwen Zhang ◽  
Fulong Wang ◽  
Weichu Xiao ◽  
...  
Keyword(s):  
Local Search ◽  
Measurement Model ◽  
Covariance Estimation ◽  
Passive Radar ◽  
Clutter Suppression ◽  
Reference Channel ◽  
Local Searches ◽  
Reference Signals ◽  
Suppression Method ◽  
Space Time Adaptive Processing

For an airborne passive radar with contaminated reference signals, the clutter caused by multipath (MP) signals involved in the reference channel (MP clutter) corrupts the covariance estimation in space-time adaptive processing (STAP). In order to overcome the severe STAP performance degradation caused by impure reference signals and off-grid effects, a novel MP clutter suppression method based on local search is proposed for airborne passive radar. In the proposed method, the global dictionary is constructed based on the sparse measurement model of MP clutter, and the global atoms that are most relevant to the residual are selected. Then, the local dictionary is designed iteratively, and local searches are performed to match real MP clutter points. Finally, the off-grid effects are mitigated, and the MP clutter is suppressed from all matched atoms. A range of simulations is conducted in order to demonstrate the effectiveness of the proposed method.

A Novel Sea Clutter Suppression Method based on Neural Network

2021 ◽  
Author(s):  
Yifei Fan ◽  
Chenxiang Li ◽  
Dongtao Li ◽  
Jieshuang Li ◽  
Jia Su ◽  
...  
Keyword(s):  
Neural Network ◽  
Clutter Suppression ◽  
Sea Clutter ◽  
Suppression Method

A Heterogeneous Clutter Suppression Method based on Subarrays

2015 ◽  
Author(s):  
Ye Dong Ye Dong ◽  
Xiaodong Han Xiaodong Han ◽  
Rui Liu Rui Liu ◽  
Chenxiao Zhang Chenxiao Zhang
Keyword(s):  
Clutter Suppression ◽  
Suppression Method

An Improved Clutter Suppression Method for Non-Sidelooking Uniform Linear Array Antennas Airborne Radar

2013 ◽  
Vol 681 ◽  
pp. 175-180
Author(s):  
Jun Zhao ◽  
Xu Hang
Keyword(s):  
Linear Array ◽  
Compensation Method ◽  
Airborne Radar ◽  
Clutter Suppression ◽  
Uniform Linear Array ◽  
Array Antennas ◽  
Compensation Methods ◽  
Suppression Method ◽  
Simulation Results ◽  
Independent Identically Distributed

The clutter distribution of airborne radar with non-sidelooking uniform linear array antennas varies with ranges and samples in different range gates are not independent identically distributed vectors, so that the statistical STAP methods degrade greatly. In this paper, an improved clutter range dependence compensation method for airborne radar with uniform linear array is proposed. This method involves in a preprocessing with ADC method to align the mainlobe of clutter spectrum in different range gates and subsequently clutter suppression in other azimuths with EDBU technology. Simulation results show the proposed method can reduce the clutter spectrum dispersion significantly and outperform conventional local compensation methods.

Knowledge-Aided Ocean Clutter Suppression Method for Sky-Wave Over-the-Horizon Radar

2018 ◽  
Vol 15 (3) ◽  
pp. 355-358 ◽  
Author(s):  
Jinfeng Hu ◽  
Cao Jian ◽  
Chen Zhuo ◽  
Huiyong Li ◽  
Julan Xie
Keyword(s):  
Clutter Suppression ◽  
Suppression Method

scholarly journals Methodology to Solve the Combination of the Generalized Assignment Problem and the Vehicle Routing Problem: A Case Study in Drug and Medical Instrument Sales and Service

2018 ◽  
Vol 9 (1) ◽  
pp. 3 ◽  
Author(s):  
Malichan Thongkham ◽  
Sasitorn Kaewman
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Routing Problem ◽  
Search Techniques ◽  
De Algorithm ◽  
Local Searches ◽  
Generalized Assignment ◽  
Linear Probability

This article presents algorithms for solving a special case of the vehicle routing problem (VRP). We define our proposed problem of a special VRP case as a combination of two hard problems: the generalized assignment and the vehicle routing problem. The different evolution (DE) algorithm is used to solve the problem. The recombination process of the original DE is modified by adding two more sets of vectors—best vector and random vector—and using two other sets—target vector and trial vector. The linear probability formula is proposed to potentially use one out of the four sets of vectors. This is called the modified DE (MDE) algorithm. Two local searches are integrated into the MDE algorithm: exchange and insert. These procedures create a DE and MDE that use (1) no local search techniques, (2) two local search techniques, (3) only the exchange procedure, and (4) only the insert procedure. This generates four DE algorithms and four MDE algorithms. The proposed methods are tested with 15 tested instances and one case study. The current procedure is compared with all proposed heuristics. The computational result shows that, in the case study, the best DE algorithm (DE-4) has a 1.6% better solution than that of the current practice, whereas the MDE algorithm is 8.2% better. The MDE algorithm that uses the same local search as the DE algorithms generates a maximum 5.814% better solution than that of the DE algorithms.

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