Moving Target Azimuth Velocity Estimation for the MASA Mode Based on Sequential SAR Images

Yang, Wei; Chen, Jie; Liu, Wei; Wang, Pengbo

doi:10.1109/jstars.2016.2641744

Cited by 19 publications

(12 citation statements)

References 20 publications

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“…As shown in Figure 2, both fd,v and fr,v are greatly influenced by passive radar geometry and target motion direction. fd,v is mainly determined by the equivalent range velocity, and fr,v is mainly influenced by the equivalent azimuth velocity [36]. Normally, as depicted in Figure 2a, the range of fd,v is from −1500 Hz to 1500 Hz when the target velocity is smaller than 220 m/s (approximately 800 km/h).…”

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confidence: 96%

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2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar

et al. 2018

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Long time coherent integration is a vital method for improving the detection ability of global navigation satellite system (GNSS)-based passive radar, because the GNSS signal is not radar-designed and its power level is very low. For aircraft detection, the large range cell migration (RCM) and Doppler frequency migration (DFM) will seriously affect the coherent processing of azimuth signals, and the traditional range match filter will also be mismatched due to the Doppler-intolerant characteristic of GNSS signals. Accordingly, the energy loss of 2-dimensional (2-D) coherent processing is inevitable in traditional methods. In this paper, a novel 2-D coherent integration processing and algorithm for aircraft target detection is proposed. For azimuth processing, a modified Radon Fourier Transform (RFT) with range-walk removal and Doppler rate estimation is performed. In respect to range compression, a modified matched filter with a shifting Doppler is applied. As a result, the signal will be accurately focused in the range-Doppler domain, and a sufficiently high SNR can be obtained for aircraft detection with a moving target detector. Numerical simulations demonstrate that the range-Doppler parameters of an aircraft target can be obtained, and the position and velocity of the aircraft can be estimated accurately by multiple observation geometries due to abundant GNSS resources. The experimental results also illustrate that the blind Doppler sidelobe is suppressed effectively and the proposed algorithm has a good performance even in the presence of Doppler ambiguity.

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confidence: 96%

“…where η, R ref , λ, f d , and f r denote the illumination time, reference range, signal wavelength, target Doppler centroid, and Doppler modulated rate, and f d and f r are derived as follows [36]:…”

Section: ( ) ( ) ( )mentioning

confidence: 99%

2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar

et al. 2018

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“…where R  is the slant range offset due to Doppler spectrum shift, and  a v R and  r v R are caused by target azimuth and range motions, respectively. According to Equation ( 9), the azimuth position offset caused by target azimuth motion is linear and changes obviously as squint angle varies, which has been adopted for azimuth velocity estimation in [30]. Similarly, linear offset of range history caused by range motion as Equation ( 10) may also provide a possibility for range velocity estimation based on sequential SAR images, which will be further explained later.…”

Section: Doppler Characteristic Of Moving Targetmentioning

confidence: 99%

“…Here, , ea thre v corresponds to the target gain attenuated by 3dB. The criterion for setting the velocity threshold , ea threshold v in [30] is the main lobe separation, not considering the effect of SCR. According to the parameters in Table 1, The filter function of quadratic phase error correction in the azimuth-frequency domain is given by…”

Section: Phase Compensation In Image Processingmentioning

confidence: 99%

Assessment of Renewable Energy Resources with Remote Sensing

Martins¹

2021

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Imaging position shift based on the multiple azimuth squint angles (MASA) mode is effective for target azimuth velocity estimation, whereas accuracy is low when target range velocity is high. In this paper, the estimation problem for both target azimuth and range velocities is considered based on the multi-channels MASA (MC-MASA) mode. Firstly, the acquisition geometry of MC-MASA mode and Doppler characteristics of a moving target are analyzed in detail, especially in squint mode. Then, for better moving target estimation, the stationary background clutter is removed using the displacement phase center antenna (DPCA) technique, and the failure in range velocity estimation with sequential SAR images is also discussed. Furthermore, a modified alongtrack interferometry (ATI) is proposed to preliminarily reconstruct the azimuth-and-range velocity map based on the MC-MASA mode. Since the velocity estimation accuracy is dependent on squint angle and signal-to-clutter ratio (SCR), the circumstances are divided into three cases with different iteration estimation strategies, which could expand the scene application scope of velocity estimation and achieve a high estimation accuracy along both azimuth and range directions. Finally, the performance of the proposed method is demonstrated by experimental results.

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“…Recently, two innovative methods were studied based on sequential SAR images [25][26][27][28][29][30], including the bi-directional (BiDi) mode [25][26][27][28][29] and the multiple azimuth squint angle (MASA) mode [30]. The BiDi mode works with two main lobes pointing to different directions simultaneously in azimuth, and the same area is observed twice with a short time lag between two acquisitions.…”

Section: Introductionmentioning

confidence: 99%

A Moving Target Velocity Estimation Method Based on the MC-MASA SAR Mode

et al. 2021

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Imaging position shift based on the multiple azimuth squint angles (MASA) mode is effective for target azimuth velocity estimation, whereas accuracy is low when target range velocity is high. In this paper, the estimation problem for both target azimuth and range velocities is considered based on the multi-channels MASA (MC-MASA) mode. Firstly, the acquisition geometry of MC-MASA mode and Doppler characteristics of a moving target are analyzed in detail, especially in squint mode. Then, for better moving target estimation, the stationary background clutter is removed using the displacement phase center antenna (DPCA) technique, and the failure in range velocity estimation with sequential SAR images is also discussed. Furthermore, a modified along-track interferometry (ATI) is proposed to preliminarily reconstruct the azimuth-and-range velocity map based on the MC-MASA mode. Since the velocity estimation accuracy is dependent on squint angle and signal-to-clutter ratio (SCR), the circumstances are divided into three cases with different iteration estimation strategies, which could expand the scene application scope of velocity estimation and achieve a high estimation accuracy along both azimuth and range directions. Finally, the performance of the proposed method is demonstrated by experimental results.

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Moving Target Azimuth Velocity Estimation for the MASA Mode Based on Sequential SAR Images

Cited by 19 publications

References 20 publications

2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar

2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar

Assessment of Renewable Energy Resources with Remote Sensing

A Moving Target Velocity Estimation Method Based on the MC-MASA SAR Mode

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