An Efficient Imaging Algorithm for GNSS-R Bi-Static SAR

Abstract

Global Navigation Satellite System Reflectometry (GNSS-R) based Bi-static Synthetic Aperture Radar (BSAR) is becoming more and more important in remote sensing, given its low power, low mass, low cost, and real-time global coverage capability. Due to its complex configuration, the imaging for GNSS-R BSAR is usually based on the Back-Projection Algorithm (BPA), which is very time consuming. In this paper, an efficient and general imaging algorithm for GNSS-R BSAR is presented. A Two Step Range Cell Migration (TSRCM) correction is firstly applied. The first step roughly compensates the RCM and Doppler phase caused by the motion of the transmitter, which simplifies the SAR data into the quasi-mono-static case. The second step removes the residual RCM caused by the motion of the receiver using the modified frequency scaling algorithm. Then, a cubic phase perturbation operation is introduced to equalize the Doppler frequency modulation rate along the same range cell. Finally, azimuth phase compensation and geometric correction are completed to obtain the focused SAR image. A simulation and experiment are conducted to demonstrate the feasibility of the proposed algorithm, showing that the proposed algorithm is more efficient than the BPA, without causing significant degradation in imaging quality.

An Image Formation Algorithm for Bistatic SAR Using GNSS Signal With Improved Range Resolution

“…So the proposed method also generates the signal phase two times superposition, which is identical to the square operation in Diff2. The rest of imaging algorithm, including direct interference cancellation, range cell migration correction and azimuth compression, can use general image formation method for GNSS-SAR, and we employ the algorithm in reference [21] in this paper. Based on the successfully verified results of one-dimensional simulation and experiment, the two-dimensional imaging will be conducted in the next section to show the improvement of range resolution performance.…”

“…The separation of passive Bi-SAR system transmitter and receiver yields several configuration using different types of transmitters or receivers, including spaceborne, airborne, ground-based system [1]- [3]. Many different types of available illuminators of opportunity can be utilized as the transmission, such as digital audio broadcasting(DAB) [4], Digital Video Broadcasting Terrestrial(DVB-T) [5]- [10], WiFi [11], DTV [12], [13], and Global Navigation Satellite Systems (GNSS) [14]- [21]. The advantages of passive bistatic radar include low cost, free license, silence working and environmental friendly, making it feasible in the earth remote sensing fields.…”

Moving Target Detection in Multi-Static GNSS-Based Passive Radar Based on Multi-Bernoulli Filter

“…The radar system's range history is a crucial factor for signal processing and target detection. Considering the link of the i-th transmitter, target and receiver, the range history Ri(η) can be modeled as [11,12] ( ) The radar system's range history is a crucial factor for signal processing and target detection. Considering the link of the i-th transmitter, target and receiver, the range history R i (η) can be modeled as [11,12] R i (η) = P Tran,i − P tar 2 + P tar 2 = R re f ,i…”

“…Compared with other opportunistic illuminators, the global navigation satellite system (GNSS) is a good choice for passive radar given its permanent global coverage, plentiful satellite resources and ease for synchronization [1][2][3][4]. Therefore, the GNSS-based passive radar (GBPR) is an innovative, all-weather, and all-time microwave tool for remote sensing and target detection applications, and it has developed very quickly in recent years [5][6][7][8][9][10][11][12][13][14][15].…”

“…To overcome the low power level for target detection in a GBPR system, advanced signal processing methods, such as SAR imaging and two-dimensional (2-D) coherent integration [10][11][12][13], are needed to achieve the 2-D coherent integration gain [14,15]. Normally, the GBPR system is based on the bi-static model, where a single GNSS satellite is used as the transmitter.…”