Entropy function optimization for radar imaging

The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking （DCT）algorithm. Since these values are obtained according to the maximum likelihood （ML） principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.

Angle estimation for bistatic MIMO radar with unknown mutual coupling based on three-way compressive sensing

The problem of angle estimation for bistatic multiple-input multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions. © 2017 Beijing Institute of Aerospace Information.

Doppler radar by using single multicarrier pulse based on optical fibre delay lines

The proposed Doppler measurement technique shows that the Doppler measurements can be accomplished by a single pulse with multiple frequency components through optical fibre delay lines.Range and velocity ambiguity can be removed,and the velocity resolution can be improved dramatically by using long optical fibre delay lines.Furthermore,the velocity resolution can be modified by adjusting the length of optical fibre delay lines.In addition,the proposed radar can achieve high range resolution by using a single wideband pulse.As a result,the new approach can improve radar performance significantly.

Array-error estimation method for multi-channel SAR systems in azimuth

For multi-channel synthetic aperture radar（SAR） systems, since the minimum antenna area constraint is eliminated,wide swath and high resolution SAR image can be achieved.However, the unavoidable array errors, consisting of channel gainphase mismatch and position uncertainty, significantly degrade the performance of such systems. An iteration-free method is proposed to simultaneously estimate position and gain-phase errors.In our research, the steering vectors corresponding to a pair of Doppler bins within the same range bin are studied in terms of their rotational relationships. The method is based on the fact that the rotational matrix only depends on the position errors and the frequency spacing between the paired Doppler bins but is independent of gain-phase error. Upon combining the projection matrices corresponding to the paired Doppler bins, the position errors are directly obtained in terms of extracting the rotational matrix in a least squares framework. The proposed method, when used in conjunction with the self-calibration algorithm, performs stably as well as has less computational load, compared with the conventional methods. Simulations reveal that the proposed method behaves better than the conventional methods even when the signal-to-noise ratio（SNR） is low.

The signal selection and processing method for polarization measurement radar

Based on the ambiguity function, a novel signal processing method for the polarization measurement radar is developed. One advantage of this method is that the two orthogonal polarized signals do not have to be perpendicular to each other, which is required by traditional methods. The error due to the correlation of the two transmitting signals in the traditional method, can be reduced by this new approach. A concept called ambiguity function matrix （AFM） is introduced based on this method. AFM is a promising tool for the signal selection and design in the polarization scattering matrix measurement. The waveforms of the polarimetric radar are categorized and analyzed based on AFM in this paper. The signal processing flow of this method is explained. And the polarization scattering matrix measurement performance is testified by simulation. Furthermore, this signal processing method can be used in the inter-pulse interval measurement technique as well as in the instantaneous measurement technique.

NEW METHOD FOR REDUCED RANK STAP—NON CLUTTER CHANNEL METHOD

For reduced-rank space-time adaptive processing(STAP) in airborne radar, this paper presents a new method — non clutter channel(NCC） method which is easy to implement in real radar systems. The NCC method uses those “channels” located in the non-clutter domain to construct the reduce-rank transformation matrix. This method avoids eigen-decomposition and the computational cost is very low. The performance is compared with that of several other methods; the simulation demonstrates that the NCC method can well approach the optimum performance and even outperform some more complex methods in low rank.

Novel polarimetric detector for target detection in heterogeneous clutter

A detection of static or slowly moving targets in the inhomogeneous clutter of polarimetric radar is researched and a new detector without exploiting the training set is developed, which has a good performance against the inhomogeneous clutter. The decision rule ensures the constant false alarm rate (CFAR) with respect to the disturbance covariance matrix. Numerical results show the robustness of the proposed method against the inhomogeneous clutter. © 2016 Beijing Institute of Aerospace Information.

Multi-function radar emitter identification based on stochastic syntax-directed translation schema

To cope with the problem of emitter identification caused by the radar words＇ uncertainty of measured multi-function radar emitters, this paper proposes a new identification method based on stochastic syntax-directed translation schema（SSDTS）. This method, which is deduced from the syntactic modeling of multi-function radars, considers the probabilities of radar phrases appearance in different radar modes as well as the probabilities of radar word errors occurrence in different radar phrases. It concludes that the proposed method can not only correct the defective radar words by using the stochastic translation schema, but also identify the real radar phrases and working modes of measured emitters concurrently. Furthermore, a number of simulations are presented to demonstrate the identification capability and adaptability of the SSDTS algorithm.The results show that even under the condition of the defective radar words distorted by noise,the proposed algorithm can infer the phrases, work modes and types of measured emitters correctly.

ABORT-like detector to combat active deceptive jamming in a network of LFM radars

This paper studies an electronic counter-counter measures（ECCM） scheme combating against deceptive electronic counter measure（ECM） techniques. An adaptive detector exploiting generalized likelihood ratio test（GRLT） criterion is applied to detect the presence of deceptive jamming in fractional Fourier transform（Fr FT） domain. First, the generating mechanism of spurious frequencies is analyzed based on the Volterra serial. The proposed nonlinear distortion model based on power amplifier behavior is robust in distortion analysis when the memory effect is considered.Second, a modified adaptive beamformer orthogonal rejection test（ABORT） like detector in closed form is built. The proposed detector can discriminate the echo and deceptive jamming adaptively by exploiting primary data and secondary data. This ECCM scheme is capable of guaranteeing the performance without the restriction of orthogonality, which is essential for the ABORT detectors. The expansion to radar network is discussed as a special case at the final part of this paper. Numerical simulations demonstrate the effectiveness of the proposed method.