Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to noise.In this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present signals.The concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA estimations.Moreover,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA estimations.Simulation results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

Full aperture imaging algorithm for highly squinted TOPS SAR

Aiming at solving the azimuth signal aliasing problem in the Doppler domain, the azimuth time aliasing problem after range cell migration correction (RCMC) and the severe range and the azimuth coupling problem in both the phase and envelope for highly squinted terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), a novel full aperture imaging algorithm is presented. An unaliased two-dimensional (2-D) spectrum is first obtained by the azimuth preprocessing; the modified range migration algorithm (RMA) is then used to complete RCMC; and finally the azimuth signal is focused in the Doppler domain by spectral analysis (SPECAN) and deramping. Simulations and real data processing results validate the effectiveness of the proposed algorithm. ? 2016 Beijing Institute of Aerospace Information.

Property analysis of bistatic forward-looking SAR with arbitrary geometry

Bistatic forward-looking synthetic aperture radar（SAR） has many advantages and applications owing to its twodimensional imaging capability.There could be various imaging configurations because of the geometric flexibility of bistatic platforms,resulting in kinds of models built independently among which there could be some similar even the same motion features.Comprehensive research on such systems in a more comprehensive and general point of view is required to address their difference and consistency.Property analysis of bistatic forwardlooking SAR with arbitrary geometry is achieved including stripmap and spotlight modes on airborne platform,missile-borne platform,and hybrid platform of both.Emphasis is placed on azimuth space variance of some key parameters significantly affecting the subsequent imaging processing,based on which the frequency spectra are further described and compared considering respective features of different platforms for frequency imaging algorithm developing.Simulation results confirm the effectiveness and correctness of our analysis.

Object Detection Research of SAR Image Using Improved Faster Region-Based Convolutional Neural Network

Target detection technology of synthetic aperture radar(SAR)imageis widely used in the field of military reconnaissance and surveillance.The traditional SAR image target detection methods need to be provided a lot of empirical knowledge because the characteristics of SAR images in different configurations(attitude,pitch angle,imaging parameters,etc.)will change greatly,resulting in high generalization error.Currently,deep learning method has achieved great success in the field of image processing.Research shows that deep learning can achieve a more intrinsic description of the data,while the model has a stronger ability of modeling and generalization.In order to solve the problem of insufficient data in SAR data sets,an experimental system for acquiring SAR image data in real scenes was built.Then the transfer learning method and the improved convolution neural network algorithm(PCA+Faster R-CNN)are applied to improve the target detection precision.Finally,experimental results demonstrate the significant effectiveness of the proposed method.

Ionosphere correction algorithm for spaceborne SAR imaging

For spaceborne synthetic aperture radar （SAR） imaging,the dispersive ionosphere has significant effects on the propagationof the low frequency （especially P-band） radar signal. Theionospheric effects can be a significant source of the phase error inthe radar signal, which causes a degeneration of the image qualityin spaceborne SAR imaging system. The background ionosphericeffects on spaceborne SAR through modeling and simulation areanalyzed, and the qualitative and quantitative analysis based onthe spatio-temporal variability of the ionosphere is given. A novelionosphere correction algorithm （ICA） is proposed to deal with theionospheric effects on the low frequency spaceborne SAR radarsignal. With the proposed algorithm, the degradation of the imagequality caused by the ionosphere is corrected. The simulation resultsshow the effectiveness of the proposed algorithm.

High-speed ground moving target detection research using triangular modulation FMCW

The frequency modulated continuous wave(FMCW)radar has the characteristics of low probability of interception,good hidden property and the ability to counter anti-radiation missiles.This paper proposes a new method for high-speed ground moving target detection(GMTD)using triangular modulation FMCW.According to the characteristic of the opposite range shift induced by the upslope and downslope modulation FMCW,the upslope and downslope are imaged,respectively.After compensation of continuous motion of the platform and time difference between upslope and downslope signals for imaging,the moving target can be detected through displaced phase center antenna(DPCA)technology.When the moving target is detected,the moving target image is extracted,and correlation processing is used to obtain the range shift,which can be used to estimate the target radial velocity,and further to find the real position of the target.The effectiveness of this method is verified by the result of computer simulation.