Microwave Staring Correlated Imaging Based on Unsteady Aerostat Platform

Abstract

Microwave staring correlated imaging (MSCI), with the technical capability of high- resolution imaging on relatively stationary targets, is a promising approach for remote sensing. For the purpose of continuous observation of a fixed key area, a tethered floating aerostat is often used as the carrying platform for MSCI radar system; however, its non-cooperative random motion of the platform caused by winds and its unbalance will result in blurred imaging, and even in imaging failure. This paper presents a method that takes into account the instabilities of the platform, combined with an adaptive variable suspension (AVS) and a position and orientation system (POS), which can automatically control the antenna beam orientation to the target area and measure dynamically the position and attitude of the stochastic radiation radar array, respectively. By analyzing the motion feature of aerostat platform, the motion model of the radar array is established, then its real-time position vector and attitude angles of each antenna can be represented; meanwhile the selection matrix of beam coverage is introduced to indicate the dynamic illumination of the radar antenna beam in the overall imaging area. Due to the low-speed discrete POS data, a curve-fitting algorithm can be used to estimate its accurate position vector and attitude of each antenna at each high-speed sampling time during the imaging period. Finally, the MSCI model based on the unsteady aerostat platform is set up. In the simulations, the proposed scheme is validated such that under the influence of different unstable platform movements, a better imaging performance can be achieved compared with the conventional MSCI method.

Microwave Staring Correlated Imaging Based on Quasi-Stationary Platform With Motion Measurement Errors

“…The measurement errors are denoted as v e = v − v m and ω e = ω − ω m . The imaging equation involving motion measurement errors can be written as Sr = S e (v e , ω e ) • σ + w (18) where S e (v e , ω e ) = S(v m + v e , ω m + ω e ).…”

“…Few studies are concentrated on the errors caused by the motion of the platform. As far as we know, only [18] proposes to compensate for the motion errors by the polynomial fitting of the data of the position and orientation system (POS). The study also points out that MSCI is sensitive to motion measurement errors.…”

“…The target image is recovered by Tikhonov regularization, and the motion measurement errors are corrected by the Newton method at each iteration. Compared with [18], this paper not only uses POS data to compensate for the motion errors, but also proposes a self-calibration imaging algorithm to estimate and correct the measurement errors. Therefore, the imaging performance of MSCI based on quasi-stationary platform is improved.…”

Microwave Staring Correlated Imaging Method Based on Steady Radiation Fields Sequence

“…By the Correlation Process (CP) of TSSRF and the corresponding scattering echo, targets within the imaging region can be reconstructed with high imaging resolution. MSCI achieves superior imaging performance without the relative motion between radar and target, and has thus attracted increasing attention and obtained rapid developments in many aspects, such as imaging algorithms [12][13][14], outfield experiments [15], imaging based on unsteady aerostat platform [16,17], etc.…”

Unmanned Aerial Vehicle-Borne Sensor System for Atmosphere-Particulate-Matter Measurements: Design and Experiments

“…However, it is fixed on spot and difficult to move, with limitations on observation range and height. The second is tethered aerostat observation, with different sensors loaded on tethered balloons to measure vertical distribution of high-level contaminants [14][15][16][17][18]. However, a tethered aerostat cannot flexibly observe in a wide range.…”