468 research outputs found

    High Speed Dim Air Target Detection Using Airborne Radar under Clutter and Jamming Effects

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    The challenging potential problems associated with using airborne radar in detection of high Speed Maneuvering Dim Target (HSMDT) are the highly noise, jamming and clutter effects. The problem is not only how to remove clutter and jamming as well as the range migration and Doppler ambiguity estimation problems due to high relative speed between the targets and airborne radar. Some of the recently published works ignored the range migration problems, while the others ignored the Doppler ambiguity estimation. In this paper a new hybrid technique using Optimum Space Time Adaptive Processing (OSTAP), Second Order Keystone Transform (SOKT), and the Improved Fractional Radon Transform (IFrRT) was proposed. The OSTAP was applied as anti-jamming and clutter rejection method, the SOKT corrects the range curvature and part of the range walk, then the IFrRT estimates the target’ radial acceleration and corrects the residual range walk. The simulation demonstrates the validity and effectiveness of the proposed technique, and its advantages over the previous researches by comparing its probability of detection with the traditional methods. The new approach increases the probability of detection, and also overcomes the limitation of Doppler frequency ambiguity

    Adaptive Radar Detection of Dim Moving Targets in Presence of Range Migration

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    This paper addresses adaptive radar detection of dim moving targets. To circumvent range migration, the detection problem is formulated as a multiple hypothesis test and solved applying model order selection rules which allow to estimate the "position" of the target within the CPI and eventually detect it. The performance analysis proves the effectiveness of the proposed approach also in comparison to existing alternatives.Comment: 5 pages, 2 figures, submitted to IEEE Signal Processing Letter

    SAR Image Formation via Subapertures and 2D Backprojection

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    Radar imaging requires the use of wide bandwidth and a long coherent processing interval, resulting in range and Doppler migration throughout the observation period. This migration must be compensated in order to properly image a scene of interest at full resolution and there are many available algorithms having various strengths and weaknesses. Here, a subaperture-based imaging algorithm is proposed, which first forms range-Doppler (RD) images from slow-time sub-intervals, and then coherently integrates over the resulting coarse-resolution RD maps to produce a full resolution SAR image. A two-dimensional backprojection-style approach is used to perform distortion-free integration of these RD maps. This technique benefits from many of the same benefits as traditional backprojection; however, the architecture of the algorithm is chosen such that several steps are shared with typical target detection algorithms. These steps are chosen such that no compromises need to be made to data quality, allowing for high quality imaging while also preserving data for implementation of detection algorithms. Additionally, the algorithm benefits from computational savings that make it an excellent imaging algorithm for implementation in a simultaneous SAR-GMTI architecture

    ΠŸΡ€ΠΎΡΡ‚ΠΎΠΉ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ компСнсации ΠΌΠΈΠ³Ρ€Π°Ρ†ΠΈΠΉ свСтящихся Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΏΠΎ Π΄Π°Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ для Ρ€Π΅ΠΆΠΈΠΌΠ° Π±ΠΎΠΊΠΎΠ²ΠΎΠ³ΠΎ ΠΎΠ±Π·ΠΎΡ€Π° РБА (Π°Π½Π³Π».)

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    Introduction.Β  Range Cell Migration (RCM) is a source of image blurring in synthetic aperture radars (SAR). There are two groups of signal processing algorithms used to compensate for migration effects. The first group includes algorithms that recalculate the SAR signal from the "along–track range – slant range" coordinate system into the "along-track rangeΒ  –  cross-track range"Β  coordinates using the method of interpolation. The disadvantage of these algorithms is their considerable computational cost. Algorithms of the second group do not rely on interpolation thus being more attractive in terms of practical application.Aim. To synthesize a simple algorithm for compensating for RCM without using interpolation.Materials and methods. The synthesis was performed using a simplified version of the Chirp Scaling algorithm.Results.Β  A simple algorithm, which presents a modification of the Keystone Transform algorithm, was synthesized. The synthesized algorithm based on Fast Fourier Transforms and the Hadamard matrix products does not require interpolation.Conclusion. A verification of the algorithm quality via mathematical simulation confirmed its high efficiency. Implementation of the algorithm permits the number of computational operations to be reduced. The final radar imageΒ  produced using the proposed algorithm is built in the true Cartesian coordinates. The algorithm can be applied for SAR imaging of moving targets. The conducted analysis showed that the algorithm yields Β theΒ  image of a moving target provided that the coherent processing interval is sufficiently large. The image lies along a line, which angle of inclination is proportional to the projection of the target relative velocity on the line-of-sight. Estimation of the image parameters permits the target movement parameters to be determined.Π’Π²Π΅Π΄Π΅Π½ΠΈΠ΅. ΠœΠΈΠ³Ρ€Π°Ρ†ΠΈΠΈ свСтящихся Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΏΠΎ Π΄Π°Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΡΠ²Π»ΡΡŽΡ‚ΡΡ источником расфокусировки Ρ€Π°Π΄ΠΈΠΎΠ»ΠΎΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈΠ·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠΉ Π² Ρ€Π°Π΄ΠΈΠΎΠ»ΠΎΠΊΠ°Ρ‚ΠΎΡ€Π°Ρ… с синтСзированной Π°ΠΏΠ΅Ρ€Ρ‚ΡƒΡ€ΠΎΠΉ (РБА). БущСствуСт Π΄Π²Π΅ Π³Ρ€ΡƒΠΏΠΏΡ‹ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠΎΠ² ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ сигналов для компСнсации ΠΌΠΈΠ³Ρ€Π°Ρ†ΠΈΠΉ. ΠŸΠ΅Ρ€Π²Π°Ρ Π³Ρ€ΡƒΠΏΠΏΠ° Π²ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΡ‹, Π² ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Π½Π° основании ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ интСрполяции осущСствляСтся пСрСсчСт принятых сигналов ΠΈΠ· систСмы ΠΊΠΎΠΎΡ€Π΄ΠΈΠ½Π°Ρ‚ "ΠΏΡ€ΠΎΠ΄ΠΎΠ»ΡŒΠ½Π°Ρ Π΄Π°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ – наклонная Π΄Π°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ"Β  Π² систСму "ΠΏΡ€ΠΎΠ΄ΠΎΠ»ΡŒΠ½Π°Ρ Π΄Π°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ – попСрСчная Π΄Π°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ". НСдостатком Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠΎΠ² Π΄Π°Π½Π½ΠΎΠΉ Π³Ρ€ΡƒΠΏΠΏΡ‹ являСтся ΠΈΡ… высокая Π²Ρ‹Ρ‡ΠΈΡΠ»ΠΈΡ‚Π΅Π»ΡŒΠ½Π°Ρ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ. Алгоритмы Π²Ρ‚ΠΎΡ€ΠΎΠΉ Π³Ρ€ΡƒΠΏΠΏΡ‹ Π½Π΅ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡŽΡ‚ интСрполяционныС ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ ΠΈ ΡΠ²Π»ΡΡŽΡ‚ΡΡ поэтому Π±ΠΎΠ»Π΅Π΅ ΠΏΡ€ΠΈΠ²Π»Π΅ΠΊΠ°Ρ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌΠΈ для практичСского использования.ЦСль.Β  Π‘ΠΈΠ½Ρ‚Π΅Π·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ простой Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ компСнсации ΠΌΠΈΠ³Ρ€Π°Ρ†ΠΈΠΉ Π±Π΅Π· примСнСния Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ интСрполяции.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. Π‘ΠΈΠ½Ρ‚Π΅Π· Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° осущСствлСн Π½Π° основании ΡƒΠΏΡ€ΠΎΡ‰Π΅Π½Π½ΠΎΠΉ вСрсии Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° Π›Π§Πœ-Ρ„ΠΈΠ»ΡŒΡ‚Ρ€Π°Ρ†ΠΈΠΈ (Chirp Scaling Algorithm).Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π‘ΠΈΠ½Ρ‚Π΅Π·ΠΈΡ€ΠΎΠ²Π°Π½ простой Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ, ΡΠ²Π»ΡΡŽΡ‰ΠΈΠΉΡΡ ΠΌΠΎΠ΄ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠ΅ΠΉ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° "Π·Π°ΠΌΠΊΠΎΠ²ΠΎΠ³ΠΎ камня".Алгоритм основан Π½Π° использовании быстрых ΠΏΡ€Π΅ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠΉ Π€ΡƒΡ€ΡŒΠ΅ ΠΈ поэлСмСнтных ΠΌΠ°Ρ‚Ρ€ΠΈΡ‡Π½Ρ‹Ρ… ΡƒΠΌΠ½ΠΎΠΆΠ΅Π½ΠΈΠΉ. Π’ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ΅ Π½Π΅ ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΡŽΡ‚ΡΡ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ интСрполяции.Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. ΠŸΡ€ΠΎΠ²Π΅Ρ€ΠΊΠ° качСства Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° Π½Π° основС матСматичСского модСлирования ΠΏΠΎΠ΄Ρ‚Π²Π΅Ρ€Π΄ΠΈΠ»Π° Π΅Π³ΠΎ Π²Ρ‹ΡΠΎΠΊΡƒΡŽ ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ. ИспользованиС Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ° позволяСт ΡƒΠΌΠ΅Π½ΡŒΡˆΠΈΡ‚ΡŒ количСство Π²Ρ‹Ρ‡ΠΈΡΠ»ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΎΠΏΠ΅Ρ€Π°Ρ†ΠΈΠΉ.ЀинальноС Ρ€Π°Π΄ΠΈΠΎΠ»ΠΎΠΊΠ°Ρ†ΠΈΠΎΠ½Π½ΠΎΠ΅ ΠΈΠ·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅, ΠΏΠΎΠ»ΡƒΡ‡Π°Π΅ΠΌΠΎΠ΅ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°, строится Π²Β  истинной Π΄Π΅ΠΊΠ°Ρ€Ρ‚ΠΎΠ²ΠΎΠΉ систСмС ΠΊΠΎΠΎΡ€Π΄ΠΈΠ½Π°Ρ‚. Алгоритм ΠΌΠΎΠΆΠ΅Ρ‚ Π±Ρ‹Ρ‚ΡŒ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ для построСния РБА ΠΈΠ·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠΉ двиТущихся Ρ†Π΅Π»Π΅ΠΉ. Π”Π°Π½Π½Ρ‹ΠΉ Π² ΡΡ‚Π°Ρ‚ΡŒΠ΅ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠΊΠ°Π·Π°Π», Ρ‡Ρ‚ΠΎ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ позволяСт ΠΏΠΎΡΡ‚Ρ€ΠΎΠΈΡ‚ΡŒ Ρ…ΠΎΡ€ΠΎΡˆΠΎ сфокусированноС ΠΈΠ·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅ двиТущСйся Ρ†Π΅Π»ΠΈ, ΠΊΠΎΠ³Π΄Π° ΠΈΠ½Ρ‚Π΅Ρ€Π²Π°Π» синтСзирования достаточно Π²Π΅Π»ΠΈΠΊ. Π˜Π·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅ двиТущСйся Ρ†Π΅Π»ΠΈ выстраиваСтся вдоль ΠΎΡ‚Ρ€Π΅Π·ΠΊΠ° прямой, ΡƒΠ³ΠΎΠ» Π½Π°ΠΊΠ»ΠΎΠ½Π° ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ ΠΏΡ€ΠΎΠΏΠΎΡ€Ρ†ΠΈΠΎΠ½Π°Π»Π΅Π½ ΠΏΡ€ΠΎΠ΅ΠΊΡ†ΠΈΠΈ ΠΎΡ‚Π½ΠΎΡΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΉ скорости Ρ†Π΅Π»ΠΈ Π½Π° линию визирования. ΠžΡ†Π΅Π½ΠΊΠ° ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΎΠ² изобраТСния позволяСт ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΠΈΡ‚ΡŒ ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€Ρ‹ двиТСния Ρ†Π΅Π»ΠΈ

    A Signal Processing Algorithm Based on 2D Matched Filtering for SSAR

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    This study discusses a smart radar antenna scanning mode that combines features of both the sector-scan mode used for conventional radar and the line-scan mode used for synthetic aperture radar (SAR) and achieves an application of the synthetic aperture technique in the conventional sector-scan (mechanically scanned) radar, and we refer to this mode as sector-scan synthetic aperture radar (SSAR). The mathematical model is presented based on the principle of SSAR, and a signal processing algorithm is proposed based on the idea of two-dimensional (2D) matched filtering. The influences of the line-scan range and speed on the SSAR system are analyzed, and the solution to the problem that the target velocity is very high is given. The performance of the proposed algorithm is evaluated through computer simulations. The simulation results indicate that the proposed signal processing algorithm of SSAR can gather the signal energy of targets, thereby improving the ability to detect dim targets

    Bistatic synthetic aperture radar imaging using Fournier methods

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