Study On Some Key Technologies Of Signal Processing For Airborne Digital Array Fire-control Radar

With the rapid development of digital technology and microelectronics integrated circuit technology,airborne radar has entered a new era of digitalization and modularization,and airborne fire-control radar is also developed from traditional active phased array system to digital array system.Digital array radar combines array antenna digitalization with array signal processing technology to improve anti-jamming and clutter suppression performance.However,the airborne digital array fire-control radar usually works in the high frequency band,and the number of array elements is huge.It is difficult to realize the digital transmitting and receiving of each T/R component unit and signal processing at the element level on the airborne radar with the existing technical conditions.Therefore,in order to improve the engineering applications of airborne digital array fire-control radar,it is necessary to reduce the dimension of digital transceiver channels and array signal processing simultaneously.In the aspect of digital transceiver channel,subarray division is the key technology to realize digital transmitting and receiving processing on subarray antenna,which can greatly improve the engineering application level of airborne digital array fire-control radar.However,subarray partition is a very complex problem in practice,which needs to be optimized by combining with technical and tactical requirements,development ability,cost requirements and other constraints.The result of subarray partition directly affects the complexity and performance of radar design.How to divide the subarray reasonably is the main problem in the design of airborne digital array fire-control radar.In array signal processing,ground clutter suppression is always a serious challenge for airborne fire-control radar in ground detection mode.The traditional airborne fire-control radar uses pulse Doppler principle for the Ground Moving Target Indicator(GMTI),which cannot detect the low speed moving target due to the influence of the main clutter.The digital array system of airborne fire-control radar provides convenient conditions for clutter suppression and low speed target detection by using space-time adaptive processing(STAP).In theory,full-dimensional STAP can achieve optimal performance.But in practice,full-dimensional STAP cannot meet the real-time processing requirements of airborne fire-control radar in complex clutter environment.Therefore,in order to promote the applications of airborne digital array fire-control radar STAP technology,it is very important to research suboptimal reduced-dimension STAP algorithm and its engineering application in GMTI.Synthetic aperture radar(SAR)imaging is an important function of the ground detection mode of airborne digital array fire-control radar.The performance index of SAR imaging is an important optimization target for the subarray division of digital array radar.Helicopter-borne digital array fire-control radar is usually mounted on the top of the main rotor mast to take advantage of terrain masking,which would cause that the echo signals are blocked periodically along the azimuth time by the rotor blades rotation.If not suppressed,such modulation will lead to serious ghost images in SAR imagery.This dissertation focuses on the technique development trend of airborne fire-control radar and our objective is to improve airborne digital array fire-control radar’s air-to-ground detection capability in complex battlefield environment.The research work of airborne digital array fire-control radar reduced-dimension processing and SAR imaging technology is carried out around the above issues.The main work can be summarized as follows.1.The subarray partition and performance evaluation of airborne digital array fire-control radar are firstly described.In the optimization of subarray partition,the technical indexes of array signal processing and radar antenna,such as low sidelobes requirement of antenna pattern,grating lobes effect and STAP performance,should not only be considered,but also be integrated into the system design to meet the overall operational efficiency of radar.In this paper,the general principle and architecture of the subarray partition are proposed by analyzing the different technical requirements in the subarray partition of airborne digital array fire-control radar.On this basis,a multi-objective genetic algorithm for subarray partition and optimization is proposed.The requirements of subarray partition are clarified by multi-objective weighted constraints and genetic coding,and the subarray architecture is optimized by genetic iteration.Finally,combined with the system function and performance requirements of multi-functional airborne digital array fire-control radar,the comprehensive performance evaluation and verification of the subarray partition result are carried out.2.STAP usually requires a large number of independent identically distributed samples and high computational complexity to calculate the optimum weight vector,which makes it difficult for practical applications in airborne phased array radar.A reduced-dimension adaptive processing method based on spatial-temporal data reconstruction is proposed to solve this problem.The spatial-temporal data matrix is firstly divided into uniform submatrices and reconstructed as a new matrix with similar rows and columns by utilizing the Kronecker product property of the steering matrix.Then,the optimal weight of the reconstructed data matrix is solved by the space-time separable filter(STSF)algorithm.Simulation analysis shows that the proposed method has the advantages of small training samples requirement,low computational complexity and fast convergence.Experimental results using the measured data indicate that the proposed method has greater moving target detection ability than the traditional STSF and extended factored approach(EFA).Furthermore,it can achieve better performance when the proposed method combines more temporal DOFs for submatrix adaptive processing under the same requirement of training samples support and computational complexity.In addition,we also apply the two-dimensional array matrix reconstruction to adaptive beamforming of rectangular digital array antenna.Simulation results show the good performance and efficiency of the proposed algorithm.3.Aiming at the detection requirements of airborne fire-control radar GMTI,an airborne digital array fire-control radar GMTI method based on sub-aperture processing is studied.We proposed a subarray level digital array airborne fire-control radar GMTI scheme,and verified the effectiveness of the proposed scheme by using digital array fire-control radar principle prototype test flight measured data.Firstly,through the analysis of GMTI processing requirements,a GMTI method based on sub-aperture processing is proposed,and the key steps involved are described,including pulse compression,channel calibration and STAP.Then,the radar system and the flight test scheme are briefly introduced,and the subarray structure of radar antenna is given.Finally,the performance improvement of signal-clutter-noise-ratio(SCNR)by STAP is quantitatively analyzed for the mainlobe region target and the sidlobe region target respectively,and the angle measurement performance by interferometry is compared with the conventional digital monopulse estimation method.The performance analysis of test flight measured data indicates that the proposed algorithm can meet the requirements of clutter suppression,angular measurement accuracy,engineering implementation complexity and system robustness,and is a reliable moving target detection method for airborne digital array fire-control radar.4.We present the demonstration of the ghost images on the armed helicopter-borne SAR.Our objective is to develop an efficient rotor blades blockage modulation echo suppression algorithm for the helicopter-borne digital array fire-control radar SAR imagery.This algorithm draws on the thought that the periodically blocked signal could be decomposed into a set of Fourier series components.After range pulse compression and motion compensation with respect to the scene centre,the SAR echo signals are expanded into the Fourier series along the azimuth direction.Then,the focused ghost image is achieved by the range and azimuth resampling procedures,while the azimuth interpolation is in a manner just the combination of the range cell migration(RCM)linearization and the keystone transform.After the blocked echo focusing,the range bins which contain the clearest information about the modulation echo are identified and extracted.Subsequently,an approximate modulation function is estimated by adopting an iterative approximation strategy which estimates the coefficient of each decomposed harmonic component one by one.Finally,the acquired approximate function is used to remove the modulation echo in each range bin.Both simulated and real-measured data are processed to demonstrate the effectiveness of the proposed algorithm.