## 2 Review  
In this section, a brief review of the current imaging framework for HRWS SAR imaging is presented. Taking the most common type of HRWS SAR system design, for example, the azimuth multichannel SAR (AMC-SAR) [22,26], its imaging model is presented in Figure 1.  
As shown in Figure 1, unlike the traditional SAR system, multiple receiving channels are deployed along the azimuth direction. Within each transmitting pulse, these receiving channels simultaneously receive echoes from the whole scene. Considering the transmitting signal as the linear frequency-modulated signal, the received signal of each channel for one point target can be expressed as  
\[S_{rb}(t,\eta,i)=A_{0}rect\Big{[}\frac{t-t_{0}(\eta)}{T_{r}}\Big{]}\exp\Big{\{} j\pi K_{r}[t-t_{0}(\eta)]^{2}\Big{\}}\exp\{-j2\pi f_{0}t_{0}(\eta)\} \tag{1}\]  
where \(t\) is the range time, \(\eta\) is the azimuth time, \(i=1,2,\ldots,N\) is the channel index and \(N\) is the number of channels, \(A_{0}\) is the target intensity, \(rect[\cdot]\) is the range envelope function, \(t_{0}(\eta)=2R_{0}(\eta)/c\) is the target instantaneous range time delay, \(R_{0}(\eta)\) is the target instantaneous slant range distance, \(c\) is the light speed, \(T_{r}\) is the pulse width, \(K_{r}\) is the frequency modulation rate of transmitting signal, and \(f_{0}\) is the carrier frequency. For  
Figure 1: Azimuth multichannel SAR imaging model.  
imaging in the range direction, matched filtering is conducted, and the imaging result in the range direction is  
\[s_{r}(t,\eta,i)=A_{0}sinc[K_{r}T_{r}(t-t_{0}(\eta))]\text{exp}\{-j2\pi f_{0}t_{0}( \eta)\} \tag{2}\]  
The next step is azimuth multichannel signal reconstruction. This step is the core step of AMC-SAR signal processing. This step allows for imaging results of all receiving channels in the range direction to be reorganized and combined into an equivalent result of traditional single-channel SAR [27]. As shown in Figure 2, the combined imaging result in the range direction is obtained through the rearranging of samples according to the azimuth time sequence and channel arrangement sequence. The antenna phase centers (APCs) of each channel are sorted into equivalent phase centers (EPCs) [28].  
The rearranged result is  
\[\begin{array}{l}s_{r}(t,\eta)=[\cdots,s_{ar}(t,\eta_{k}),s_{ar}(t,\eta_{k+1}) \cdots]\\ s_{ar}(t,\eta_{k})=[s_{r}(t,k\cdot\text{PRT},1),s_{r}(t,k\cdot\text{PRT},2),s_{ r}(t,k\cdot\text{PRT},3)]\\ s_{ar}(t,\eta_{k+1})=[s_{r}(t,(k+1)\cdot\text{PRT},1),s_{r}(t,(k+1)\cdot\text{PRT },2),s_{r}(t,(k+1)\cdot\text{PRT},3)]\end{array} \tag{3}\]  
where \(k\) is the pulse index and PRT is the pulse repetition period. After multichannel signal reconstruction, azimuth imaging methods for traditional SAR can be utilized, such as range-Doppler [29] and BP [30; 31]. For wide-swath imaging, BP has some unique advantages. First, for a wide-swath scene, range-Doppler has the limitation of the imaging area's size due to its approximated model of the range history, while this is not a problem for BP due to its accurate model [32]. Second, for online processing, range-Doppler has an online update limitation due to its need for the whole aperture, and this is not a problem for BP due to its ability of time-domain subaperture accumulation [31]. Third, for online processing, BP can be implemented in parallel through graphical processing units (GPU). Fourth, for platforms with maneuverability, BP can be implemented with a nonlinear trajectory [19]. Due these advantages, we prefer BP as the azimuth imaging method. Thus, the final imaging result after BP is  
\[I(m,n)=\int_{T_{A}}s_{r}(t,\eta)\exp\{j2\pi f_{0}t_{0}(\eta)\}d\eta \tag{4}\]  
where \(m\) and \(n\) are the image's azimuth and range pixel index, respectively, and \(T_{A}\) is the synthetic aperture time. The current imaging framework for HRWS imaging is summarized and illustrated in Figure 3.  
Figure 2: Azimuth multichannel signal reconstruction illustration.