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Student Number 85247005
Author Jin-Min Kuo(i)
Author's Email Address No Public.
Statistics This thesis had been viewed 2355 times. Download 1210 times.
Department Graduate Institute of Space Science
Year 2001
Semester 2
Degree Ph.D.
Type of Document Doctoral Dissertation
Language English
Title The estimator for Estimating Target Velocity with SAR
Date of Defense 2002-06-17
Page Count 78
Keyword
  • doppler coefficients
  • finite difference
  • phas
  • SAR
  • Synthetic aperture radar
  • Abstract A moving target will change the coefficients of the synthetic aperture radar (SAR) chirp signals. Vice versa, the velocity could be inferred from the SAR images or signals. This paper proposes two algorithms for estimating a moving targets velocity in the SAR image or signal. Topic-1 describes the velocity estimation of a moving target in the SAR signals; Topic-2 describes that in the SAR images.
    Topic-1 describes a new approach for estimating the Doppler coefficients from a finite number of noisy discrete-time observations, which are functions of the speed variation of target/radar. The approach adopts the finite difference method to estimate the chirp signal coefficients. It is motivated with the concept of the HAF. But the finite difference method directly calculates the phase of the signal. The finite difference method, with respect to the HAF, replaces the correlation operations with addition and average operations. That reduces the computation load. A closed-form expression is derived that describes the relationship between the phase differences and the chirp signal parameters. The difference method could derive the phase differences, but cause the deterioration of the signal variance. The finite difference method is a good way to reduce the noise deviations, but the measurable spans will become smaller. The measurable span could be improved by adopting a phase unwrapping method, as proposed in Topic-1. Unwrapping the phase differences could recover the chirp signal coefficients from bias estimates. The maximum measurable span of the coefficients will be significantly larger. The statistical analysis for the finite difference estimation proves that the variance could attain the Cramer-Rao lower bounds in higher SNR. In conclusion, our algorithm can reduce the computational complexity and remove the effect of the signal amplitude variation.
    A moving ship on SAR image produces multiscale wake with a characteristic linear V-shaped pattern. Detection of the wake can provide substantial information about the ship, such as its size, direction and speed of movement. In general, ship-generated wakes in SAR images are associated with high sea clutter, which causes the deterioration of detection performance. Topic-2 presents a hybrid method that combines the wavelet technique and the Radon transforms technique to detect the ship wake. The wavelet technique is first applied to generate a set of multiscale images. An orthogonal basis function is adopted so that three high-pass images in horizontal, vertical and diagonal direction are generated for each resolution scale. Then a spatial correlator is applied among the moduli of different scale, where modulus images are formed from three high-pass images. The output of the correlation process is shown to be highly representative at ship wake edges. Comparisons with other methods indicate the superior performance of the present approach in that not only are the wakes detected but also the V-shaped pattern is well pre-served. The second stage of the method involves the application of the Radon transform technique to estimate the V-opening angle from the detected ship wakes. Compared with a direct Radon transform, the greater effectiveness of the proposed scheme is demonstrated in a terms of efficiency as well as reliability for ship wake detection in noisy backgrounds.
    Table of Content Chapter 1 IntroductionKKKKKKKKKKKKKKKKKKKKKK.K.1
    1.1 Estimator in SAR signalsKKKKKKKKKKKKKKKKKK.KK1
    1.2 Estimator in SAR imagesKKKKKKKKKKKKKKKKK.KK...3
    1.3 Organization of the dissertationKKKKKKKKKKKKKKK..KK4
    Chapter 2 Synthetic aperture radarKKKKKKKKKKKKKKKKK.K...8
    2.1 Synthetic apertureKKKKKKKKKKKKKKKKKKKK.KK..8
    2.1.1 Concept of synthetic apertureKKKKK.KKKKKKKKKKK.8
    2.1.2 Target/radar range variationKKKKK.KKKKKKKKK...KK.9
    2.2 Synthetic aperture radar processingKKKKK...KKKKKKKKKK12
    2.2.1 Matched filterKKKKK...KKKKKKKKKKKKKKKK..12
    2.2.2 Range compressionKKKKK...KKKKKKKKKKKKKK.15
    2.2.3 Azimuth compressionKKKKKKKKKKKKKKKK...KK.16
    Chapter 3 Moving target velocity estimation in SAR signalsKKKKKK...K..18
    3.1 Estimation method for chirp signal coefficients KKKK KKKKK.K.18
    3.1.1 Finite difference estimationKKK KKKKKKKKKKKK.K..18
    3.1.2 Enlarge measurable spanKKKKKKKKKKKK.KKK.K.K.26
    3.1.2.1 Two- delay parameters finite differenceKKK KKKKK.KK26
    3.1.2.2 Phase unwrappingKKKKKKKKKKKKKKKKKK....27
    3.2 Measurable span of the velocityKKKKKKKKKKKKKKKKK28
    3.3 Statistical analysis of finite difference algorithmKK KKKKK..K...K31
    3.3.1 High SNR approximationKKKKKKK..K..KKKKK...KKK31
    3.3.2 Mean square error of finite difference algorithmKKKKK KKK..33
    3.4 SimulationsKKK K..KKKKKKKKKKKKKKKKKKKK.38
    Chapter 4 Moving target velocity estimation in SAR imagesKKKKKKKK.47
    4.1 Ship Wake SystemKKKKKKKKKKKKKKKK..KKKKK..47
    4.2 Ship Wake Detection via the Wavelet TechniqueKKKKKK..KKK..49
    4.2.1 Basics of Wavelet TransformKKKKKKKKKKK..KK.KK..49
    4.2.2 Spatial correlator based on modulusKKKKKKK..K..KKK.K.51
    4.2.3 Detection Results: Simulated imagesKKKKKKKKKKKKK.52
    4.3 Estimate the V-opening angleKKKKKKKKKKKKKKKK.K..65
    4.3.1 Radon Transform Technique as an Angle EstimatorKKKKKKK.65
    4.3.2 Simulation resultsKKKKKKKKKKKKKKKKKKK.K..67
    4.3.3 Real SAR image testKKKKKKKKKKKKKKKKKK.K.71
    Chapter 5 Conclusions and Further research...................KKKKKKK.KK..73
    5.1 Estimator in SAR signals...........KKKKKKK.KKKKKKKKK..73
    5.1.1 Summary and Main Contribution...........KKKKKKK.KKKK...73
    5.1.2 Suggestion for Future Research...........KKKKKKK.KKKKK.73
    5.2 Estimation Method in SAR images...........KKKKKKK.KKK.KK..74
    References KKKKKKKKKKKK............KKKKKKK.KKK.KK..75
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    Advisor
  • K. S. Chen(Cs)
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    Date of Submission 2002-07-16

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