KEYWORDS: Matrices, Image deconvolution, Detection and tracking algorithms, Scattering, 3D modeling, Synthetic aperture radar, Imaging arrays, Signal to noise ratio, Point spread functions, 3D image processing
A synthetic aperture radar three-dimensional imaging system based on frequency diversity array (3D-FDA-SAR) has the characteristics of low cost and flexible transmission signal and is used in 3D imaging of complex environments. However, due to the range-angle dependence of the frequency diversity array (FDA), the information in each dimension will be coupled with each other when imaging the target, and the space-time-frequency sparse characteristic of the echo signal leads to high side lobes in the imaging results. In this paper, the deconvolution algorithm is applied to the imaging of 3D-FDA-SAR, the coupling is removed according to the coupling generation characteristics, and the effect of reducing side lobes is achieved at the same time. Using MATLAB simulation and comparing the simulation results with the simulation using the BP algorithm directly, the results show that the 3D-FDA-SAR after adding the algorithm in this paper has a better effect on multi-target imaging and is more suitable for the real imaging environment.
A range-angle–dependent beam pattern can be produced by frequency diversity array (FDA) due to the small frequency offsets between the array elements. The beam pattern can be used to automatically scan an area in its entirety and estimate the distance and angle to a target. However, for constant tracking of the target after recognition, energy is wasted in the scanning mode because of periodic scanning of the main lobe of the beam. To eliminate this energy waste, we propose multiple repeated subpulses of FDA. This scheme achieves stable tracking without range–angle coupling. This special transmission method considerably improves the transmission energy and signal-to-noise ratio, while ensuring accurate range detection and high resolution. The results of a feasibility analysis and simulation experiments verify the superiority of the proposed method.
Aiming at optimizing the allocation problem of limited resources in a radar network, a resource scheduling algorithm combining pulse interleaving with preallocation is proposed for multitarget inverse synthetic aperture radar imaging. The imaging method adopts compressed sensing, which only needs to emit a small number of pulses so that we can set the algorithms to schedule the allocation of the pulses over a period of time. The authors point out the problem of pulse conflict, which is ignored in the process of the scheduling algorithm and proposes a preallocation method to avoid the occurrence of the conflict. Meanwhile, pulse interleaving is added to increase the positions of the dispatchable pulses. Moreover, the combined algorithm can perform adaptive scheduling on the radar time resource according to the feature parameters after target feature cognitive. Finally, the feasibility of the combined algorithm is verified by the simulation, and two performance indicators, the hit value rate and the pulse utilization rate, are improved by the proposed algorithm.
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