scholarly journals Transmitted Waveform Design Based on Iterative Methods

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Bin Wang ◽  
Jinkuan Wang ◽  
Xin Song ◽  
Fengming Xin
Keyword(s):  
Mutual Information ◽  
Iterative Methods ◽  
Interior Point ◽  
Interior Point Method ◽  
Optimization Problem ◽  
Waveform Design ◽  
Design Criterion ◽  
Cognitive Radar ◽  
Simulation Results ◽  
Transmitted Waveform

In intelligent radar, it is an important problem for the transmitted waveform to adapt to the environment in which radar works. In this paper, we propose mutual information model of adaptive waveform design, which can convert the problem of adaptive waveform design into the problem of optimization. We consider two situations of no clutter and clutter and use Newton method and interior point method to solve the optimization problem. Then we can draw the design criterion for the transmitted waveform in cognitive radar and get a greater mutual information from the simulation results. Finally, the whole paper is summarized.

scholarly journals Robust Waveform Design Based on Bisection and Maximum Marginal Allocation Methods with the Concept of Information Entropy

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Bin Wang ◽  
Xiaolei Hao
Keyword(s):  
Mutual Information ◽  
Optimization Design ◽  
Waveform Design ◽  
Observation Time ◽  
Cognitive Radar ◽  
Bisection Algorithm ◽  
Water Filling ◽  
Water Filling Algorithm ◽  
Concept Of Information ◽  
Transmitted Waveform

Cognitive radar can overcome the shortcomings of traditional radars that are difficult to adapt to complex environments and adaptively adjust the transmitted waveform through closed-loop feedback. The optimization design of the transmitted waveform is a very important issue in the research of cognitive radar. Most of the previous studies on waveform design assume that the prior information of the target spectrum is completely known, but actually the target in the real scene is uncertain. In order to simulate this situation, this paper uses a robust waveform design scheme based on signal-to-interference-plus-noise ratio (SINR) and mutual information (MI). After setting up the signal model, the SINR and MI between target and echo are derived based on the information theory, and robust models for MI and SINR are established. Next, the MI and SINR are maximized by using the maximum marginal allocation (MMA) algorithm and the water-filling method which is improved by bisection algorithm. Simulation results show that, under the most unfavorable conditions, the robust transmitted waveform has better performance than other waveforms in the improvement degree of SINR and MI. By comparing the robust transmitted waveform based on SINR criterion and MI criterion, the influence on the variation trend of SINR and MI is explored, and the range of critical value of Ty is found. The longer the echo observation time is, the better the performance of the SINR-based transmitted waveform over the MI-based transmitted waveform is. For the mutual information between the target and the echo, the performance of the MMA algorithm is better than the improved water-filling algorithm.

scholarly journals Multi-Target Robust Waveform Design Based on Harmonic Variance and Mutual Information

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Bin Wang ◽  
Shuangqi Yu
Keyword(s):  
Mutual Information ◽  
Design Method ◽  
Waveform Design ◽  
Upper And Lower Bounds ◽  
Cognitive Radar ◽  
Multiple Targets ◽  
Uncertainty Range ◽  
Target Spectrum ◽  
Definition Of ◽  
Transmitted Waveform

Cognitive radar is an intelligent radar system, and adaptive waveform design is one of the core problems in cognitive radar research. In the previous studies, it is assumed that the prior information of the target is known, and the definition of target spectrum variance has not changed. In this paper, we study on robust waveform design problem in multiple targets scene. We hope that the upper and lower bounds of the uncertainty range of robustness are more close to the actual situation, and establish a finite time random target signal model based on mutual information (MI). On the basis of the optimal transmitted waveform and robust waveform based on MI, we redefine the target spectrum variance as harmonic variance, and propose a novel robust waveform design method based on harmonic variance and MI. We compare its performance with robust waveform based on original variance. Simulation results show that, in the situation of multiple targets, compared to the original variance, the MI lifting rate of robust waveform based on harmonic variance relative to the optimal transmitted waveform in the uncertainty range has great improvement. In certain circumstances, robust waveform based on harmonic variance and MI is more suitable for more targets.

scholarly journals Adaptive Radar Waveform Design Based on Weighted MI and the Difference of Two Mutual Information Metrics

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fengming Xin ◽  
Bin Wang ◽  
Shumin Li ◽  
Xin Song ◽  
Chi-Hsu Wang
Keyword(s):  
Mutual Information ◽  
Impulse Response ◽  
Waveform Design ◽  
Adaptive Radar ◽  
Trade Offs ◽  
Power Spectral ◽  
Simulation Results ◽  
The Difference ◽  
Transmitted Waveform ◽  
Information Metrics

This study deals with the problem of radar waveform design based on the weighted mutual information (MI) and the difference of two mutual information metrics (DMI) in signal-dependent interference. Since the target and clutter information are included in the received signal at the beginning of the design, DMI-based waveform is designed according to the following criterion: maximizing the MI between the received signal and target impulse response while minimizing the MI between the received signal and the clutter impulse response. This criterion is equivalent to maximizing the difference between the first MI and the second MI. Then maximizing the difference of two types of MI is used as the objective function, and the optimization model with the transmitted waveform energy constraint is established. In order to solve it, we resort to maximum marginal allocation (MMA) method to find the DMI-based waveform. Since DMI-based waveform does not allocate energy to the frequency band where the clutter power spectral density (PSD) is greater than the target PSD, we propose to weight the MI-based waveform and DMI-based waveform to synthesize the final optimal waveform. It could provide different trade-offs between two types of MI. Simulation results show the proposed algorithm is valid.

scholarly journals Heat transfer from convecting-radiating fin through optimized Chebyshev polynomials with interior point algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 102-110
Author(s):  
Elyas Shivanian ◽  
Mahdi Keshtkar ◽  
Hamidreza Navidi
Keyword(s):  
Heat Transfer ◽  
Chebyshev Polynomials ◽  
Interior Point ◽  
Interior Point Method ◽  
Optimization Problem ◽  
Mathematical Formulation ◽  
Interior Point Algorithm ◽  
Equivalent Problem ◽  
One Dimensional ◽  
Fin Efficiency

AbstractIn this paper, the problem of determining heat transfer from convecting-radiating fin of triangular and concave parabolic shapes is investigated.We consider one-dimensional, steady conduction in the fin and neglect radiative exchange between adjacent fins and between the fin and its primary surface. A novel intelligent computational approach is developed for searching the solution. In order to achieve this aim, the governing equation is transformed into an equivalent problem whose boundary conditions are such that they are convenient to apply reformed version of Chebyshev polynomials of the first kind. These Chebyshev polynomials based functions construct approximate series solution with unknown weights. The mathematical formulation of optimization problem consists of an unsupervised error which is minimized by tuning weights via interior point method. The trial approximate solution is validated by imposing tolerance constrained into optimization problem. Additionally, heat transfer rate and the fin efficiency are reported.

Interior-Point Method for the Computation of Shakedown Loads for Engineering Systems

2010 ◽  
Author(s):  
Jaan-Willem Simon ◽  
Dieter Weichert
Keyword(s):  
Interior Point ◽  
Interior Point Method ◽  
Optimization Problem ◽  
Specific Problem ◽  
Practical Interest ◽  
Solution Procedure ◽  
Interior Point Algorithm ◽  
Engineering Systems ◽  
Shakedown Analysis ◽  
Convex Optimization Problem

A new interior-point algorithm for the computation of shakedown loads has recently been developed by the authors. The analytical formulation is based on the statical shakedown theorem by Melan which leads to a nonlinear convex optimization problem. The algorithm’s efficiency results from the close adaption of the solution procedure to the specific problem of shakedown analysis. This paper focuses on algorithmic aspects of the proposed method. A numerical example of practical interest is used for validation purposes.

OFDM waveform design based on mutual information for cognitive radar applications

2018 ◽  
Vol 75 (5) ◽  
pp. 2518-2534 ◽  
Author(s):  
Vahid Karimi ◽  
Reza Mohseni ◽  
Sadegh Samadi
Keyword(s):  
Mutual Information ◽  
Waveform Design ◽  
Cognitive Radar ◽  
Radar Applications

Mutual Information Model of Adaptive Waveform Design

2011 ◽  
Vol 460-461 ◽  
pp. 207-212
Author(s):  
Bin Wang ◽  
Jin Kuan Wang ◽  
Xin Song
Keyword(s):  
Mutual Information ◽  
Working Conditions ◽  
Information Model ◽  
Waveform Design ◽  
Radar Systems ◽  
Simulation Results

Traditional radar systems are lack of adaptivity to the environment. Modern radar systems should transmit different waveforms according to different environment. In this paper, mutual information model of adaptive waveform design is proposed. With this model, different waveforms can be designed adaptively under different radar working conditions. Simulation results demonstrate the validity of our model. Finally, the whole paper is summarized.

scholarly journals Waveform Design for Improved Detection of Extended Targets in Sea Clutter

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3957
Author(s):  
Linke Zhang ◽  
Na Wei ◽  
Xuhao Du
Keyword(s):  
Closed Loop ◽  
Waveform Design ◽  
Optimization Criterion ◽  
Clutter Suppression ◽  
Sea Clutter ◽  
Cognitive Radar ◽  
Extended Target ◽  
Loop Feedback ◽  
Closed Loop Feedback ◽  
Transmitted Waveform

Adaptive waveform design for cognitive radar in the case of extended target detection under compound-Gaussian (CG) sea clutter is addressed. Based on the CG characteristics of sea clutter, the texture component is employed to characterize the clutter ensemble during each closed-loop feedback and its estimation can be used for the next transmitted waveform design. The resulting waveform design problem is formulated according to the following optimization criterion: maximization of the output signal-to-interference-plus-noise ratio (SINR) for sea clutter suppression, and imposing a further constraint on sidelobes level of the waveform autocorrelation outputs for decreasing the false alarm rate. Numerical results demonstrate the effectiveness of this approach.

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