# Estimating the Observation Area of a Stripmap SAR via an ISAR Image Sequence
The linear structural features of space target components are used in [11; 12; 13], the rectangular structure features of the space targets are used in [14; 15], and the cuboid or cylindrical structural features of space targets are used in [16]. This type of algorithm utilizes the special structural feature constraints of the space targets to establish the estimation objective function, and achieves good estimation performance under the condition of a high signal-to-noise ratio (SNR). However, these algorithms usually require high-quality ISAR images when extracting special structural features; that is, the SNR must be high enough. In addition, the projection of linear structure and rectangular structure under certain observational perspectives may be a point and a line, which leads to failure in structural feature extraction and further affects the attitude estimation of space target. (3) Machine learning methods. With the development of artificial intelligence technology, some scholars have applied artificial intelligence algorithms to the attitude estimation of space targets and achieved some research results [17; 18]. However, it is difficult to establish a perfect electromagnetic simulation model for non-cooperative space targets, so it is hard to obtain the massive set of training samples required by machine learning algorithms, which leads to difficulties in obtaining good estimation performance and limits the wide application of artificial intelligence technology in the field of space target attitude estimation. There is almost no relevant research in the existing literature that directly estimates the time-varying area observed by spaceborne SARs operating in stripmap mode. In this article, we parameterize the time-varying area observed by a spaceborne SAR operating in stripmap mode into a fixed attitude of the spaceborne SAR's antenna. Then, we construct an objective function by applying the principle of minimizing the dihedral angle between the plane containing the estimated scatterers of the parabolic antenna edge and the plane containing the actual parabolic antenna edge of the spaceborne SAR to estimate the fixed attitude of the spaceborne SAR's antenna. Therefore, we can estimate the area observed by the spaceborne SAR in stripmap mode by estimating the fixed attitude of the spaceborne SAR antenna. The innovations of this article are as follows:  
1. One-to-one correspondence is established between the time-varying area observed by the spaceborne SAR operating in boresight stripmap mode and the look angle of the spaceborne SAR's antenna, which provides a new approach to estimating the time-varying area observed by spaceborne SARs operating in boresight stripmap mode. 2. According to the ISAR imaging model for spaceborne SAR, a concise expression of the ISAR projection matrix is obtained via matrix derivation. 3. The proposed algorithm has no special constraints on the antenna structure of the spaceborne SAR, and is only based on the coplanarity of the scatterers on the parabolic antenna edge or the panel antenna of the spaceborne SAR. In addition, an objective function to estimate the look angle of the spaceborne SAR operating in boresight stripmap mode is established, according to the principle of minimizing the dihedral angle between the plane containing the ideal estimated scatterers and the plane containing the actual parabolic antenna edge. 4. Based on the coplanarity of the scatterers on the parabolic antenna edge of a spaceborne SAR, it is easy to obtain an accurate normal vector of the antenna edge datum plane. In addition, using the dihedral angle to construct the objective function, the characteristic is obvious, the performance is stable, and the algorithm has good robustness. The rest of this article is organized as follows.