Using radar sea echo to estimate surface layer refractivity profiles

Rogers, L.T.; Hattan, C. P.; Krolik, Jeffrey L.

doi:10.1109/igarss.1999.773597

Cited by 4 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fortunately, a successful example, Wallops98, was provided in [1]. In this paper, the experimental data used to test the retrieval algorithm referring to [11].…”

Section: Experimental Datamentioning

confidence: 99%

“…And an experiment (called Wallops98) was carried out to estimate parameters of atmospheric ducts from radar clutter, whose results show the feasibility and efficiency [1][2][3] of the RFC technique. For the great important applications of atmospheric ducts, recently, many Chinese researchers have started researches on relevant theories, such as happening mechanism [4][5][6][7], occurrences probability [8,9] and effects of ducts on radio systems [7,10], and gotten some results of retrieval [11].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Retrieving Evaporation Duct Heights From Radar Sea Clutter Using Particle Swarm Optimization (Pso) Algorithm

Bo¹,

Wu²,

Zhao³

et al. 2009

PIER M

View full text Add to dashboard Cite

Abstract-Particle Swarm Optimization algorithm (PSO) is a popular stochastic searching optimization algorithm to solve complicated optimization problems. The approach of retrieving duct parameters from the sea-surface reflected radar clutter is also known as Refractivity From Clutter (RFC) technique. RFC technique provides the near-real-time duct parameters to evaluate the radio system performance, without adding any hardware. Basic principles of PSO and its applications and RFC technique are introduced. Evaporation duct is retrieved based on RFC technique using PSO. The performance of PSO is validated using experiment data launched at East China Sea and compared with those of genetic algorithm (GA) and ant colony algorithm (ACA). The results indicate that PSO has the advantages of faster convergence and higher retrieval precision than the other two methods.

show abstract

“…Fortunately, a successful example, Wallops98, was provided in [1]. In this paper, the experimental data used to test the retrieval algorithm referring to [11].…”

Section: Experimental Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Retrieving Evaporation Duct Heights From Radar Sea Clutter Using Particle Swarm Optimization (Pso) Algorithm

Bo¹,

Wu²,

Zhao³

et al. 2009

PIER M

View full text Add to dashboard Cite

show abstract

“…Attempts have been made to invert the problem and under some circumstances it may be possible to infer the propagation conditions from the observed clutter returns. This technique is known as refractivity from clutter [18,19].…”

Section: Characterising Sea Cluttermentioning

confidence: 99%

Challenges in radar sea clutter modelling

Watts

Rosenberg

2022

IET Radar Sonar & Navi

View full text Add to dashboard Cite

The ability to detect small targets in sea clutter is still an ongoing challenge, even for modern radar systems. Over the past decade, the development of new radar waveforms and signal processing algorithms has been assisted by an increasingly good understanding of the characteristics of sea clutter. Nevertheless, many challenges remain in the development of robust sea clutter models that span the wide range of sea conditions and viewing geometries encountered in practice. This paper describes the current challenges with some suggestions on how they can be overcome.

show abstract

“…Atmospheric ducts can change the propagation characteristics of electromagnetic waves such as a significant change in the maximum operational radar range, creations of radar holes and an increase in the sea clutter and so on [1][2][3][4][5] . Hence, radio systems/radar systems operating in these environments would benefit from the knowledge of the effects of the environment on their system performance.…”

Section: Introductionmentioning

confidence: 99%

Performance comparison of GA, PSO, and DE approaches in estimating low atmospheric refractivity profiles

Wang

Zhao³

2010

Wuhan Univ. J. Nat. Sci.

View full text Add to dashboard Cite

Particles swarm optimization (PSO) and differential evolution (DE) algorithms based on optimization are employed to estimate low atmospheric refractivity profiles from radar sea clutter. Low atmospheric refractivity profiles are modeled as evaporation ducts. The objective functions, which are used to evaluate the fit of simulated and measured power in estimation procedures, are also investigated at different frequencies such as L-, S-, C-and Xfrequency at 10 m/s wind speeds. The results show that all the objective functions are multi-peak functions. The Adjusted Barton Model of radar cross section (RCS) is adopted. PSO and DE algorithms are compared with genetic algorithm (GA) by 200 Monte Carlo simulation estimations. Simulation results indicate that DE has the best global search ability, and PSO has the highest success probability. According to the statistical results, PSO algorithm with the population size 30 is the appropriate way for evaporation duct estimation.

show abstract

Using radar sea echo to estimate surface layer refractivity profiles

Cited by 4 publications

References 6 publications

Retrieving Evaporation Duct Heights From Radar Sea Clutter Using Particle Swarm Optimization (Pso) Algorithm

Retrieving Evaporation Duct Heights From Radar Sea Clutter Using Particle Swarm Optimization (Pso) Algorithm

Challenges in radar sea clutter modelling

Performance comparison of GA, PSO, and DE approaches in estimating low atmospheric refractivity profiles

Contact Info

Product

Resources

About