## 2 Geometry and Signal Model
### Signal Model
\right] \tag{9}\]  
Its compact form is:  
\[\mathbf{S}_{Z}=\mathbf{A}_{Z}\mathbf{J}+\mathbf{G}_{Z}, \tag{10}\]  
where \(\mathbf{J}=\left[ \begin{array}{cccc}j_{1}^{1}(t_{r},t_{a})&\ldots&j_{1}^{K }(t_{r},t_{a})\end{array} \right]^{T}\) denotes the matrix composed of interference signals from K RFI sources received by channel \(z_{1}\), and \(\mathbf{G}_{Z}=\left[ \begin{array}{cccc}g_{z1}(t_{r},t_{a})&\ldots&g_{zM}(t_ {r},t_{a})\end{array} \right]^{T}\) is the equivalent additive noise matrix of the M channels on the \(Z\)-axis, the steering matrix \(\mathbf{A}_{Z}\) is:  
Figure 2: The schematic diagram of the signal from the \(k\)-th RFI source being received by channel \(z_{1}\) and \(z_{m}\). The time difference between the same RFI signal arriving at these two channels is \(\tau_{zm}^{k}\). \[\mathbf{A}_{Z}=\left[ \begin{array}{cccc}e^{-i2\pi f_{c}x_{11}^{x}}&e^{-i2\pi f_{ c}x_{12}^{x}}&\ldots&e^{-i2\pi f_{c}x_{12}^{x}}\\ e^{-i2\pi f_{c}x_{12}^{x}}&e^{-i2\pi f_{c}x_{22}^{x}}&\ldots&e^{-i2\pi f_{c}x_{2 2}^{x}}\\ \vdots&\vdots&\ddots&\vdots\\ e^{-i2\pi f_{c}x_{1M}^{1}}&e^{-i2\pi f_{c}x_{2M}^{2}}&\ldots&e^{-i2\pi f_{c}x_{ 2M}^{K}}\end{array} \right]. \tag{11}\]  
In accordance with Equation (7) and the signal wavelength \(\lambda=\frac{C}{f_{c}}\), \(\mathbf{A}_{Z}\) can be further transformed into:  
\[\mathbf{A}_{Z}=\left[ \begin{array}{cccc}1&1&\ldots&1\\ e^{-i2\pi\frac{d}{\lambda}\cos^{\theta}1}&e^{-i2\pi\frac{d}{\lambda}\cos^{ \theta}2}&\ldots&e^{-i2\pi\frac{d}{\lambda}\cos^{\theta}K}\\ \vdots&\vdots&\ddots&\vdots\\ e^{-i2\pi\frac{(M-1)d}{\lambda}\cos^{\theta}1}&e^{-i2\pi\frac{(M-1)d}{ \lambda}\cos^{\theta}2}&\ldots&e^{-i2\pi\frac{(M-1)d}{\lambda}\cos^{\theta}K} \end{array} \right]. \tag{12}\]  
Similarly, the signals received by channel \(y_{2}\) to \(y_{M}\) on the \(Y\)-axis can be expressed as:  
\[\mathbf{S}_{Y}=\mathbf{A}_{Y}\mathbf{J}+\mathbf{G}_{Y}, \tag{13}\]  
where \(\mathbf{S}_{Y}=\left[ \begin{array}{cccc}s_{y2}(t_{r},t_{a})&\ldots&s_{yM}(t_ {r},t_{a})\end{array} \right]^{T}\), \(\mathbf{G}_{Y}=\left[ \begin{array}{cccc}g_{y2}(t_{r},t_{a})&\ldots&g_{yM}(t_ {r},t_{a})\end{array} \right]^{T}\) is the equivalent additive noise matrix of the M channels on the \(Y\)-axis. The time difference of the \(k\)-th RFI signal to channel \(y_{1}\) and to channel \(y_{m}\) is \(\tau_{ym}^{k}\), it can be represented as:  
\[\tau_{ym}^{k}=\frac{(m-1)d\sin^{k}\cos\varphi^{k}}{C}. \tag{14}\]  
Similar to \(\mathbf{A}_{Z}\), \(\mathbf{A}_{Y}\) is the steering matrix of the M channels on the \(Y\)-axis, and the divergence between them is the time difference. Therefore, based on Equation (14), \(\mathbf{A}_{Y}\) can be written as:  
\[\mathbf{A}_{Y}=\left[ \begin{array}{cccc}e^{-i2\pi\frac{d}{\lambda}\sin^{ \theta}\cos\varphi^{1}}&e^{-i2\pi\frac{d}{\lambda}\sin\theta^{2}\cos\varphi^{2} }&\ldots&e^{-i2\pi\frac{d}{\lambda}\sin\theta^{k}\cos\varphi^{k}}\\ e^{-i2\pi\frac{2d}{\lambda}\sin^{\theta}\cos\varphi^{1}}&e^{-i2\pi\frac{2d}{ \lambda}\sin\theta^{2}\cos\varphi^{2}}&\ldots&e^{-i2\pi\frac{2d}{\lambda}\sin \theta^{k}\cos\varphi^{k}}\\ \vdots&\vdots&\ddots&\vdots\\ e^{-i2\pi\frac{(M-1)d}{\lambda}\sin\theta^{1}\cos\varphi^{1}}&e^{-i2\pi\frac{ (M-1)d}{\lambda}\sin\theta^{2}\cos\varphi^{2}}&\ldots&e^{-i2\pi\frac{(M-1)d}{ \lambda}\sin\theta^{k}\cos\varphi^{k}}\end{array} \right]. \tag{15}\]  
Finally, the signals of all channels form the SAR echo signal matrix \(\mathbf{S}\):  
\[\mathbf{S}=\left[ \begin{array}{cccc}\mathbf{S}_{Z}\\ \mathbf{S}_{Y}\end{array} \right]=\left[ \begin{array}{cccc}\mathbf{A}_{Z}\\ \mathbf{A}_{Y}\end{array} \right]\mathbf{J}+\left[ \begin{array}{cccc}\mathbf{ G}_{Z}\\ \mathbf{G}_{Y}\end{array} \right]=\mathbf{A}\mathbf{J}+\mathbf{G}, \tag{16}\]  
where \(\mathbf{A}=\left[ \begin{array}{cccc}\mathbf{A}_{Z}&\mathbf{A}_{Y}\end{array}  \right]^{T}\) and \(\mathbf{G}=\left[ \begin{array}{cccc}\mathbf{G}_{Z}&\mathbf{G}_{Y}\end{array}  \right]^{T}\).