This article proposes CORPS beamforming network (BFNs) with both beam and null steering capability. All simulation results are presented for scannable mono‐beam configuration but it can be extended to the multi‐beam system. Complex inputs are optimised by means of the PSO algorithm to get the array factor with the desired characteristics that are side lobe level (SLL), directivity (D), and null depth. All sub‐blocks of the BFN are designed in the centre frequency of 2.4 GHz.

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Tomographic imaging of a dynamic scene is addressed for the first time in this article. The effect of dynamics of the imaged object is studied for some deformation scenarios using the conventional truncated singular value decomposition (TSVD) method, which is applied in numerous static inverse scattering problems, together with variational data assimilation (DA) methods including three-dimensional variational (3D-VAR) and four-dimensional variational (4D-VAR) techniques. Results show that the DA frameworks outperform the TSVD method, which assumes the scene static, especially for objects with higher contrast. Also, it is seen that applying the conventional TSVD method makes the image blurred and distorts it for high-speed dynamic changes, particularly when the contrast is increased. However, the proposed DA methods seem to be robust against large deformation distortions and can still detect the object.