| 1. |
- Jamil, Momin, et al.
(author)
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Cross-ambiguity function of weighted pulse trains with Oppermann sequences
- 2009
-
Conference paper (peer-reviewed)abstract
- The design of integrated radar and communication systems may be based on sets of polyphase sequences such as Oppermann sequences. In this paper, we derive an analytical expression for the cross-ambiguity function of weighted pulse trains with Oppermann sequences. Further, the auto-ambiguity function is deduced from this as a special case. Numerical examples are provided to illustrate the relationship between sequence parameters and performance characteristics.
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| 2. |
- Jamil, Momin, et al.
(author)
-
Levy Flight Based Cuckoo Search Algorithm for Synthesizing Cross-Ambiguity Functions
- 2013
-
Conference paper (peer-reviewed)abstract
- The cross-ambiguity function (CAF) is commonly used to analyze the delay-Doppler characteristics of signals in radar, sonar, and communication systems. Accordingly, a CAF relates to the correlation processing of signals in the presence of delays and Doppler shifts. In this paper, we use a metaheuristic approach to address the CAF synthesis problem by jointly designing a pair of waveforms. The CAF of waveforms designed in this way, approximates a desired pre-defined CAF. It turns out that the waveforms designed by this approach have the benefit of low peak-to-average power ratios. Numerical examples are presented to show that nature-inspired metaheuristic algorithms can be used as an effective tool to synthesize different types of CAFs.
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| 3. |
- Jamil, Momin, et al.
(author)
-
Levy Flights and Global Optimization
- 2013
-
In: Swarm Intelligence and Bio-Inspired Computation. - London : Elsevier. - 9780124051638 ; , s. 49-72
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Book chapter (peer-reviewed)abstract
- A review of metaheuristic algorithms (MAs) is presented. Levy flights (LFs) in the context of global optimization, the Levy distribution, a method to generate random numbers within this distribution are discussed. Subsequently, diversification and intensification in global optimization based on LFs are discussed. Then, MAs using LFs as a search mechanism to solve global optimization problems are presented along with highlighting the differences and similarities of different MAs.
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| 4. |
- Jamil, Momin, et al.
(author)
-
Multimodal function optimisation with cuckoo search algorithm
- 2013
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In: International Journal of Bio-Inspired Computation (IJBIC). - : Interscience Publishers. - 1758-0366 .- 1758-0374. ; 5:2, s. 73-83
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Journal article (peer-reviewed)abstract
- Modern engineering and scientific optimisation problems are becoming complicated. In order to cope with the increasing level of difficulty of these problems, optimisation methods are required to find more than one solution to these problems. The aim of this paper is to gain an insight into the ability of cuckoo search to locate more than one solution for multimodal problems. We also study the performance of this algorithm in the additive white Gaussian noise. Numerical results are presented to show that the cuckoo search algorithm can successfully locate multiple solutions in both non-noise and additive white Gaussian noise with relatively high degree of accuracy.
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| 5. |
- Jamil, Momin, et al.
(author)
-
Multimodal function optimization using an improved bat algorithm in noise-free and noisy environments
- 2017. - 10
-
In: Modeling and Optimization in Science and Technologies. - Cham : Springer. ; , s. 29-49
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Book chapter (peer-reviewed)abstract
- Modern optimization problems in economics, medicine, and engineering are becoming more complicated and have a convoluted search space with multiple minima. These problems are multimodal with objective functions exhibiting multiple peaks, valleys, and hyperplanes of varying heights. Furthermore, they are nonlinear, non-smooth, non-quadratic, and can have multiple satisfactory solutions. In order to select a best solution among several possible solutions that can meet the problem objectives, it is desirable to find many such solutions. For these problems, the gradient information is either not available or not computable within reasonable time. Therefore, solving such problems is a challenging task. Recent years have seen a plethora of activities to solve such multimodal problems using non-traditional methods. These methods are nature inspired and are becoming popular due to their general applicability and effective search strategies. In this chapter, we assess the ability of an improved bat algorithm (IBA) to solve multimodal problems in noise-free and additive white Gaussian noise (AWGN) environments. Numerical results are presented to show that the IBA can successfully locate multiple solutions in both noise-free and AWGN environments with a relatively high degree of accuracy. © Springer International Publishing AG 2017.
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| 6. |
- Jamil, Momin, et al.
(author)
-
On Integrated Radar and Communication Systems Using Oppermann Sequences
- 2008
-
Conference paper (peer-reviewed)abstract
- In this paper, we consider the design of integrated radar and communication systems that utilize weighted pulse trains with the elements of Oppermann sequences serving as complex-valued weights. An analytical expression of the ambiguity function for weighted pulse trains with Oppermann sequences is derived. Given a family of Oppermann sequences, it is shown that the related ambiguity function depends only on one sequence parameter. This property simplifies the design of the associated weighted pulse trains as it constrains the degrees of freedom. In contrast to the single polyphase pulse compression sequences that are typically deployed in radar applications, the families considered in this paper form sets of sequences. As such, they readily facilitate also multiple-access in communication systems. Numerical examples are provided that show the wide range of options offered by Oppermann sequences in the design of integrated radar and communication systems.
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| 7. |
- Jamil, Momin, et al.
(author)
-
Performance Assessment of Polyphase Pulse Compression Codes
- 2008
-
Conference paper (peer-reviewed)abstract
- The performance of conventional polyphase pulse compression codes such as the Frank, Frank-Zadoff-Chu (FZC), P1, P2, P3, P4, and Px codes will be compared with Oppermann codes. While the majority of the former code classes focus on radar applications, Oppermann codes have been discussed only within the context of code-division multiple-access (CDMA) systems. In this paper, we therefore consolidate findings on the conventional codes and extend the performance assessment to Oppermann codes by accounting for Doppler shifts as needed in radar applications. It is shown that Oppermann codes can conceptually support integrated radar and communication systems as compared to the P1, P2, P3, P4, and Px codes where this is not readily feasible. The numerical results given here illustrate that Oppermann codes outperform Px codes in the presence of Doppler shifts as supported by the ambiguity function.
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| 8. |
- Jamil, Momin, et al.
(author)
-
Properties of ambiguity functions for weighted pulse trains with oppermann sequences
- 2009
-
Conference paper (peer-reviewed)abstract
- In this paper, we consider properties of the autoambiguity and cross-ambiguity functions of weighted pulse trains with Oppermann sequences. Several properties are examined and proved which in turn allows for reducing the design space for optimization of a particular design. The insights gained from these properties are consolidated in a formal framework leading to procedures that can be used for a more structured waveform design. Numerical examples are provided to illustrate the relationship between sequence parameters and performance characteristics.
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| 9. |
- Jamil, Momin, et al.
(author)
-
Sequence Design for Radar Applications Using Particle Swarm Optimization
- 2016
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In: PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR COMMUNICATIONS (ATC). - : IEEE. - 9781509027118 ; , s. 210-214
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Conference paper (peer-reviewed)abstract
- Performance of polyphase sequences in radar applications can be evaluated using measures including autocorrelation function, integrated sidelobe ratio (ISLR), and peak-tosidelobe ratio (PSLR). In this paper, we adopt particle swarm optimization to find optimal parameters of Oppermann sequences such that sequences with optimal ISLR and PSLR are generated. This class of sequences has been chosen as it allows to design for a wide range of correlation characteristics by essentially controlling three parameters. A sequence design example is provided in order to illustrate that particle swarm optimization is indeed well-suited to produce optimal sequence designs with respect to the considered performance measures.
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| 10. |
- Jamil, Momin, et al.
(author)
-
Sequence optimization for integrated radar and communication systems using meta-heuristic multiobjective methods
- 2017
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In: 2017 IEEE Radar Conference, RadarConf 2017. - : Institute of Electrical and Electronics Engineers Inc.. - 9781467388238 ; , s. 0502-0507
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Conference paper (peer-reviewed)abstract
- In real-world engineering problems, several conflicting objective functions have often to be optimized simultaneously. Typically, the objective functions of these problems are too complex to solve using derivative-based optimization methods. Integration of navigation and radar functionality with communication applications is such a problem. Designing sequences for these systems is a difficult task. This task is further complicated by the following factors: (i) conflicting requirements on autocorrelation and crosscorrelation characteristics; (ii) the associated cost functions might be irregular and may have several local minima. Traditional or gradient based optimization methods may face challenges or are unsuitable to solve such a complex problem. In this paper, we pose simultaneous optimization of autocorrelation and crosscorrelation characteristics of Oppermann sequences as a multiobjective problem. We compare the performance of prominent state-of-the-art multiobjective evolutionary meta-heuristic algorithms to design Oppermann sequences for integrated radar and communication systems. © 2017 IEEE.
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