This paper proposes a method on high-frequency vibration compensation of helicopter-borne synthetic aperture radar (SAR) in terahertz band. The SAR signal model with platform vibration is established based on the mechanism of a helicopter's vibration. Then successive Doppler keystone transform (SDKT) is used to correct the range cell migration induced by the vibration. Finally, the analytical formula of the platform vibration phase error is given as well as its compensation to achieve a focused image.

For multi-target tracking in heavily cluttered environment, the number of measurement-to-track association hypotheses in each scan grows rapidly in traditional centralized multi-sensor multiple hypothesis tracking (CMS-MHT) method, which leads that the uncertainty of data association greatly increases such that correct association can hardly be given using traditional track score resulting in high leakage rate and effects of track splitting. Based on the space distribution characteristics of false alarm and target measurement when the sensor measurement error is small, this paper proposes a new angle aided CMS-MHT method, which designs angle aided track score computation to reduce the uncertainty of measurement-to-track association. In such a way, the proposed angle aided CMS-MHT can provide better association hypotheses compared with traditional CMS-MHT. Experiment results illustrate that angle aided CMS-MHT reduces leakage rate and has better track integrity in heavily cluttered environment.

In space-time adaptive processing (STAP), if incorporating a priori knowledge, the covariance matrix estimation and detection performance can be substantially improved with the heterogeneous environment effects being reduced. In addition, besides the employed priori information, the commonly exhibiting persymmetric structure in radar systems with symmetrically spaced linear array and pulse train can also be used to improve the STAP performance. In this paper, by exploiting the structure property of the covariance matrix, we propose a new knowledge-aided method which requires fewer samples and computes fully adaptive such that we can obtain the minimum mean square error estimate of the interference-plus-noise covariance matrix. At last, numerical simulations illustrate the effectiveness of the newly proposed method.

The instability of helicopter flight brings motion errors in the conventional synthetic aperture radar (SAR) imaging. Combined with terahertz (THz) technology, the influence of range migration and low frequency motion error can be significantly reduced. However, it leads the system to be extremely sensitive to platform vibration, which causes paired echoes and deteriorates image quality. A method on platform vibration compensation is proposed in this paper. On the basis of the analytic formula derivation in 2-D frequency domain for the signal, Keystone transform is employed to perform range migration correction. Then platform vibration is compensated in range-Doppler domain. Finally, deghosted images are obtained. The simulation results validate the effectiveness.

Since closely moving targets exist extensively in the ground moving target tracking, the uncertainty of data association greatly increases making the measurement-to-track association more difficult. Especially, traditional multiple hypothesis tracking (MHT) has high false tracking rate and track swap. This paper first investigates the measurement based factor graph in data association, and gives the corresponding message passing algorithm. Then, a factor graph aided multiple hypothesis tracking (FGA-MHT) method is proposed, which introduces factor graph based m-best hypothesis producing technique and exploits factor graph based probability refinement algorithm to reduce the uncertainty of measurement-to-track association. Experiment results demonstrate that FGA-MHT reduces times of track swap and increases the correct data association rate in closely moving target tracking.

Radio Frequency Interference (RFI) can deteriorate imaging quality of low frequency band synthetic aperture radar (SAR). For SAR using Linear Frequency Modulation (LFM) signals, this paper proposes an RFI suppression method based on clutter estimation in range frequency domain. This method uses eigen-decomposition to complete RFI detection and gets the maximum likelihood estimation (MLE) of clutter intensity for imaging scene. After determining spectrum intervals of RFI signals by the judging method of threshold, our method uses wiener filter to filter the RFI signals in the range frequency domain. The processing results of L-band SAR data verify the effectiveness of our method.