Due to the larger orbital arc and longer synthetic aperture time in medium Earth orbit (MEO) synthetic aperture radar (SAR), it is difficult for conventional SAR imaging algorithms to achieve a good imaging result. An improved higher order nonlinear chirp scaling (NLCS) algorithm is presented for MEO SAR imaging. First, the point target spectrum of the modified equivalent squint range model-based signal is derived, where a concise expression is obtained by the method of series reversion. Second, the well-known NLCS algorithm is modified according to the new spectrum and an improved algorithm is developed. The range dependence of the two-dimensional point target reference spectrum is removed by improved CS processing, and accurate focusing is realized through range-matched filter and range-dependent azimuth-matched filter. Simulations are performed to validate the presented algorithm.
Based on the symmetrically distributed array (SDA) structure and the resultant generalised conjugate symmetric property
of its optimum weight vector, a transformation matrix is introduced to preprocess the received array data, after which the
original complex-valued optimum weight vector is reduced to a real-valued one, so that in the following weight adaptation
we can simply remove imaginary part of the weight vector. As a result of this regularization, improved performance is
achieved with much lower computational complexity. There is an undetermined phase factor in the transformation matrix
and two different cases are studied with beamforming examples provided for each case, supported by simulation results.
In wideband beam steering, when we need to change the beam direction frequently, the most convenient and flexible way
is through digital circuits via FIR/IIR filtering. However this becomes infeasible when the signal frequency and bandwidth
are extremely high. To solve this problem, instead of sampling the signals in the temporal domain for digital processing, we
sample the signals spatially with more sensors positioned behind the original array of sensors. The spatially sampled signals
are then processed using simple analogue circuits (variable gain amplifiers) to form the required steering delays. The delay
between the spatially sampled signals is dependent on the sensor spacing and the directions of the designed beams, and is
not limited by signal frequency. Design examples are provided to show that different delays can be effectively realised by
a spatial filtering system to steer a nominal beam to required directions.