Abstract
When a stepped-frequency radar is used to obtain the high-resolution range profile (HRRP) of high-speed target, accurate speed estimation and motion compensation must be considered. Therefore, in this paper, a novel mathematical method is presented for estimating the target speed. Firstly, the pulse Doppler method is used to calculate the initial estimation value. Secondly, based on the initial estimation value, the minimum entropy method is used to calculate the coarse estimation value. Finally, based on the coarse estimation value, the minimuml1-Norms method is used to calculate the accurate estimation value. The numeric simulation results confirm that this new method is effective and predominant, which has a much higher estimation accuracy in a low SNR and a much larger estimation range of target speed. The final estimation value can be used to well compensate for the influence of target speed on HRRP.
Highlights
Stepped-frequency (SF) signal is widely used in the highresolution radar systems [1–3], because it can be used to get the high-resolution range profile (HRRP) of target
According to the discussion above, the influence of target motion on HRRP is embodied in the additional linear phase term (LPT) and quadratic phase term (QPT)
This simulation experiment proves that the estimation accuracy of Minimum l1-Norms Algorithm (MNA) is very high than that of Pulse Doppler Algorithm (PDA) and Minimum Entropy Algorithm (MEA), and it can be used to compensate results in LPT in very low signal-to-noise ratio (SNR)
Summary
Stepped-frequency (SF) signal is widely used in the highresolution radar systems [1–3], because it can be used to get the high-resolution range profile (HRRP) of target. In the literature [6, 7], based on time domain and waveform entropy, two speed estimation methods are presented They have low estimation accuracy and are only effective in a high signal-to-noise ratio (SNR) and low-speed moving targets. In the literature [8], based on SF and pulse Doppler radar signal, an effective algorithm of speed estimation is presented. Simulation results show that this method has a higher estimation accuracy and better antinoise performance It will increase the complexity of radar system. The speed estimation of superspeed moving targets in extremely low SNR is still a key problem for SF signal. It can be applied in engineering application.
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