New imaging algorithm for range resolution improvement in passive Global Navigation Satellite System‐based synthetic aperture radar

Abstract

This study proposes a new imaging algorithm for passive Global Navigation Satellite System-based synthetic aperture radar to improve range resolution. In the proposed algorithm, to reduce range compressed pulse mainlobe ambiguity caused by pseudo-random noise code frequency, second-order differentiation is carried out to the square of range compressed signal with respect to range delay lag. Because the carrier phase value is distorted in the squaring procedure, thereafter, a recovery processing is applied to each identified range compressed pulse for preserving the carrier phase for azimuth compression. Both simulation and experimental results indicate that compared to the conventional imaging algorithm, a significant enhancement in range resolution can be achieved by the proposed imaging algorithm. Meanwhile, from the results, the proposed algorithm will not degrade the compressed scene illumination level.

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

“…The Diff2 method is used on the square of range compressed signal [39], and the triangle-like range envelop of compressed signal can be sharpened by using second-order differentiation operator.…”

“…Then, the Diff2 of R 2 with respect to each range compressed pulse delay τ i can be carried out [39],…”

“…In this section, the proposed image formation algorithm for range resolution improvement of GNSS-based SAR is introduced in detail. The range compression algorithm is modified based on the Diff2 method proposed in the current research [39], which is also introduced here for comparison. One-dimensional compression of GPS-based SAR is tested by simulation and experiment using conventional cross-correlation method and Diff2 method, and the emerging problem will be discussed.…”

“…As for the phase recovery for the azimuth compression, which is similar to the derivation of the method in reference [39], the differentiation operation is dependent to range delay τ i only, so it only processes the compressed signal envelop, and will not affect the signal phase after differentiation. The phase recovery function H azi (t a , τ ) actually takes the phase distortion into consider, which is due to the square operation on the range comprressed signal.…”

“…A dual matched filtering was applied on the joint of band of E5-Q signal, and the range resolution can be improved with side-lobes suppression. In the same year, Zheng et al [39] proposed a new GPS-based SAR imaging algorithm to improve range resolution. A second-order differentiation (Diff2) operator was applied on the square of range compressed signal with respect to range delay lag, and phase value was reserved by recovery processing.…”