MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation

Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm

A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.

Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method

Opportunistic radar imaging using a multichannel receiver

Bistatic Synthetic Aperture Radars have a physically separated transmitter and receiver where one or both are moving. Besides the advantages of reduced procurement and maintenance costs, the receiving system can sense passively while remaining covert which offers obvious tactical advantages. In this work, spaceborne monostatic SARs are used as emitters of opportunity with a stationary ground-based receiver. The imaging mode of SAR systems over land is usually a wide-swath mode such as ScanSAR or TOPSAR in which the antenna scans the area of interest in range to image a larger swath at the expense of degraded cross-range resolution compared to the conventional stripmap mode. In the bistatic geometry considered here, the signals from the sidelobes of the scanning beams illuminating the adjacent sub-swath are exploited to produce images with high cross-range resolution from data obtained from a SAR system operating in wide-swath mode. To achieve this, the SAR inverse problem is rigorously formulated and solved using a Maximum A Posteriori estimation method providing enhanced cross-range resolution compared to that obtained by classical burst-mode SAR processing. This dramatically increases the number of useful images that can be produced using emitters of opportunity. Signals from any radar satellite in the receiving band of the receiver can be used, thus further decreasing the revisit time of the area of interest. As a comparison, a compressive sensing-based method is critically analysed and proves more sensitive to off-grid targets and only suited to sparse scene. The novel SAR imaging method is demonstrated using simulated data and real measurements from C-band satellites such as RADARSAT-2 and ESA’s satellites ERS-2, ENVISAT and Sentinel-1A. In addition, this thesis analyses the main technological issues in bistatic SAR such as the azimuth-variant characteristic of bistatic data and the effect of imperfect synchronisation between the non-cooperative transmitter and the receiver

Research progress on geosynchronous synthetic aperture radar

Based on its ability to obtain two-dimensional (2D) high-resolution images in all-time and all-weather conditions, spaceborne synthetic aperture radar (SAR) has become an important remote sensing technique and the study of such systems has entered a period of vigorous development. Advanced imaging modes such as radar interferometry, tomography, and multi-static imaging, have been demonstrated. However, current in-orbit spaceborne SARs, which all operate in low Earth orbits, have relatively long revisit times ranging from several days to dozens of days, restricting their temporal sampling rate. Geosynchronous SAR (GEO SAR) is an active research area because it provides significant new capability, especially its much-improved temporal sampling. This paper reviews the research progress of GEO SAR technologies in detail. Two typical orbit schemes are presented, followed by the corresponding key issues, including system design, echo focusing, main disturbance factors, repeat-track interferometry, etc, inherent to these schemes. Both analysis and solution research of the above key issues are described. GEO SAR concepts involving multiple platforms are described, including the GEO SAR constellation, GEO-LEO/airborne/unmanned aerial vehicle bistatic SAR, and formation flying GEO SAR (FF-GEO SAR). Due to the high potential of FF-GEO SAR for three-dimensional (3D) deformation retrieval and coherence-based SAR tomography (TomoSAR), we have recently carried out some research related to FF-GEO SAR. This research, which is also discussed in this paper, includes developing a formation design method and an improved TomoSAR processing algorithm. It is found that GEO SAR will continue to be an active topic in the aspect of data processing and multi-platform concept in the near future

Passive Synthetic Aperture Radar Imaging Using Commercial OFDM Communication Networks

Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection model is defined and signal processing approaches are proposed providing practical solutions to passive SAR imaging scenarios. Finally, experimental SAR images using general OFDM and WiMAX waveforms are shown to validate the overarching signal processing concept

Synthetic aperture imagery for high-resolution imaging sonar

Synthetic aperture sonar (SAS) can provide high-resolution underwater images. Traditional fast imaging algorithms designed for multi-receiver synthetic aperture sonar (MSAS) are complex because the point target reference spectrum (PTRS) deduction and imaging algorithm development are complicated. This paper proposes an imaging algorithm for the MSAS system to solve this issue. The proposed method first approximates the two-round slant range based on the phase center approximation method. The PTRS, including the quasi-monostatic and bistatic deformation terms, can be easily deduced. After compensating for the bistatic deformation term based on the interpolation and complex multiplication with the preprocessing step, the MSAS imagery can be simplified to the focus of the traditional monostatic SAS. Therefore, the conventional imaging algorithms designed for traditional monostatic SAS can be used directly. The proposed method providing high-resolution imaging results is more efficient than the traditional methods