Moving targets detection and imaging for multichannel terrain observation by progressive scans (TOPS) synthetic aperture radar ground moving targets indication (SAR-GMTI) has important application prospects. However, the azimuth bandwidth of the background clutter is much larger than the instantaneous signal bandwidth. Therefore, the background clutter will be highly aliased if the pulse repetition frequency (PRF) is limited. Direct application of space-time adaptive processing (STAP) techniques will significantly compromise the clutter suppression performance. Hence, we propose a space-time adaptive processing method based on spectrum compression. The spectrum compression process can reduce the azimuth bandwidth of the background clutter to the instantaneous signal bandwidth. Space-time adaptive processing is then performed to effectively suppress the clutter, and the clutter suppression performance is greatly improved. Furthermore, Deramp processing is used to focus the moving target in order to avoid the target ambiguities arising from the Doppler shift. Meanwhile, we can perform the moving targets tracking by utilizing the highly overlapping full-aperture images which are obtained by the TOPS SAR mode. Simulation results validate the effectiveness of the proposed algorithm.
A wide bandwidth continuous time ΣΔADC is widely used in the wireless communication field. A ΣΔADC with the 3 order 4bit modulator is designed with the 256MHz sampling frequency. In order to reduce the clock jitter, the nonreturn-to-zero (NRZ) DAC feedback pulse is used. And the loop asynchronous problem is improved by introducing a half of clock cycle delay. Also how to reduce the effect of the DAC mismatch is discussed. A low voltage, low power, and high speed operational amplifier is designed with feedforward compensation technology. Finally, based on the 0.13μm technology, the SNDR is 62.5dB and DR is 71dB with a 1.2V supply.
In the forwarding and control separation network, we model the user-priority virtual network embedding problem as an integer linear programming, which is achieved with resource grabbing and re-mapping aiming at maximizing the resource utilization of the substrate physical network. And we propose a modified discrete particle swarm optimization algorithm (M_DPSO) for short to solve the VN embedding problem. In the M_DPSO, the particle evolves more directionally, and the mutually exclusive factor of different particle positions is introduced to resolve the problem of premature and easily becoming local optimal solution. Finally, the performance parameters, including node resource utilization, link resource utilization, the VN accept rate, the average jump number and the long-term operators benefit cost ratio, are evaluated by emulation experiments. In contrast to the greedy algorithm and binary particle swarm optimization algorithm, the M_DPSO is verified to be of high performance.
For the problem of evaluating countermeasure effectiveness against the adaptive nulling antenna, the evaluating method using the analytic hierarchy process (AHP) is proposed. First, evaluating indexes of countermeasure effectiveness are selected and the hierarchical structure model is established. Then, the method of evaluating countermeasure effectiveness is obtained by using the AHP. Finally, the performance indexes of three classical adaptive nulling algorithms are evaluated with various space jammings. The results of simulation show that the method can evaluate different countermeasure means reasonably and effectively, and it also has a strong adaptability. The research can be not only used in optimizing countermeasure means and their effectiveness evaluation, but also helpful for improving the anti-jamming technology of the adaptive nulling antenna.
To cope with malicious behavior in cognitive radio networks such as providing false spectrum information and seizing spectrum resources, this paper proposes a behavior trust fuzzy evaluation model. With spectrum sensing behavior and spectrum utilization behavior as two evaluation factors, this model implements nodes' trust evaluation using the fuzzy comprehensive evaluation and decision method based on subjectivity and uncertainty of trust. In cooperative spectrum sensing, this model identifies malicious nodes based on the result of comprehensive evaluation to eliminate false feedback. In spectrum allocation, this model uses the definition of the lattice degree of nearness between fuzzy sets to calculate the difference between the actual comprehensive evaluation set and the ideal comprehensive evaluation set, and thereby quantifies the trustworthiness of non-malicious nodes and, combining with the multi-target optimization algorithm, determines the spectrum resources to be allocated to these nodes. This mechanism inhibits malicious behavior while encouraging cooperative behavior of nodes, thus achieving a joint design for spectrum sensing at the physical layer and spectrum allocation at the MAC layer. Simulation results and analysis show that the proposed model outperforms existing models in the system's sensing performance, throughput and fairness of spectrum allocation under malicious attacks.
A direction of arrival (DOA) estimation method based on a new sparse representation model of the covariance matrix is proposed. Without requiring the prior-knowledge on the noise level, the proposed method only utilizes partial information on the covariance matrix for the DOA estimation and provides robustness to noise at the cost of a tiny aperture loss. Although the proposed method is based on the statistical information on samples (i.e., covariance matrix), its principle is different from that of the traditional high-resolution DOA estimation methods (e.g., MUSIC, CAPON). The proposed method can effectively distinguish the signal sources with any coherence without decorrelation processing.
Due to its special imaging geometry, the highly squinted Terrain Observation by Progressive Scans (TOPS) SAR imaging mode is confronted with two main issues: severe range-azimuth coupling caused by high squint angles and azimuth spectrum aliasing caused by the steered azimuth beam. To solve these issues, a full aperture imaging algorithm based on the modified range migration algorithm (RMA) and spectral analysis (SPECAN) is proposed in this paper. Firstly, the two-dimensional (2-D) spectrum without aliasing is obtained by azimuth preprocessing. Then the modified RMA is used to complete range cell migration correction (RCMC) and range compression. Finally, the signal is focused in the Doppler domain by SPECAN and Deramping. Simulations and real data processing results validate the effectiveness of the proposed algorithm.
To design large space deployable antennas with lightweight and stable cable-net structures, a form-finding method is presented to design equal tension cable networks. The nodes of the networks are regarded as the points that move on the ideal reflective surface. The nodes move on the ideal surfaces of the mesh antennas under the action of the resultant forces acting on the nodes, and the tensions in the cables remain equivalent. After a period of movement, the resultant forces acting on the nodes decrease to zero gradually, and the whole system is considered to be in equilibrium. The unstrained length of each cable can be determined according to the deformed length of the cable and the tension force in the cable. A numerical example of a hoop truss cable-net antenna was calculated, and the equal tension cable structure of the mesh antenna was obtained, whose equilibrium state was validated by the finite element method. The calculated results show that the method presented is accurate, valid and feasible. The calculated results are compared with the calculated results based on the minimum norm method and the equal force density method, which shows that the mechanical performance of the network that was obtained using the equal tension method is better than that by using the other two methods. The method can be used to design the cable-net structures of space mesh antennas.
A new low leakage 3×VDD-tolerant electrostatic discharge (ESD) detection circuit only using the low-voltage device is proposed in a 90nm 1.2V CMOS process. Gate leaky characteristics of the nanoscale MOSFET and the feedback technique are used to control the trigger MOSFET and turn on the clamp device silicon-controlled rectifier (SCR). The multi-stage stacked-transistors structure is used to sustain a high voltage stress. The proposed detection circuit can generate 38mA current to turn on the clamp device SCR under the ESD stress. Under normal 3×VDD operating conditions, all the devices are free from over-stress voltage threat. The leakage current is 52nA under the 3×VDD bias at 25℃. Simulation result shows that the circuit can be successfully used for the 3×VDD-tolerant I/O buffer.
In geosynchronous earth orbit synthetic aperture radar(GEO SAR), because of such factors as the curve track of the satellite, the influence of earth rotation and so on, there is no explicit expression for the moving track of the satellite with respect to the target, and the track velocity varies greatly on different obit positions of the satellite, so the method of calculating resolution for uniform line motion in airborne and LEO SAR is not suitable for GEO SAR. Aiming at the mentioned problems, this paper proposes a method of calculating the two-dimensional spatial resolution based on phase gradient analysis in GEO SAR. In this paper, a conjecture is presented and proved by introducing the intermediate value theorem. There exists an equal track velocity, which can ensure the theoretical azimuth resolution within a range, and that azimuth resolution range is calculated. Finally, the Back projection (BP) algorithm simulation experiments validate the proposed method.
Elliptic Curve Cryptography algorithm, which depends on the difficulty of the discrete logarithm problem, has some characteristics of low computational overhead and high security. The main operation of Elliptic Curve Cryptography is point multiplication which is the most time-consuming part in the encryption and decryption process. This paper optimizes the point multiplication, proposes a hardware architecture to implement Elliptic Curve Cryptography algorithm and designs encryption and decryption system basing on FGPA. The proposed method improves the encryption and decryption efficiency by the multiplication, squaring and division optimization in the finite binary field. Analysis and testing show that the proposed architecture has some advantages with low hard resource consumption, low complexity of module interface and scalability, the designed encryption and decryption system supports key length of 113bit, 163bit, 193bit and so on, and relative to the software Elliptic Curve Cryptography system running on embedded processor, this encryption and decryption processor can achieve thousands of times faster.
An adaptive bacterial foraging optimization algorithm is presented due to the classic optimization algorithm's poor performance when optimizing high-dimensional complex functions. The fixed chemotactic step is improved as the adaptive sliding step which decreases nonlinearly with the result of strengthening the ability of local search. The adaptive dimension learning method for the optimal bacterium in the current cycle of chemotaxis is proposed so as to increase the accuracy of the solution and enhance the search efficiency. The elite bacterium is used as the initial point for Tent chaotic mapping to initialize the position of bacteria which meet the conditions of migration, and therefore the convergence speed of the algorithm is accelerated. Experimental result indicates that the algorithm outperforms the classic algorithm both in terms of solution accuracy and convergence speed. And, the algorithm has a higher efficiency.
As an emerging optical molecular imaging technology, fluorescence molecular tomography can efficiently reconstruct concentrations and three dimensional distributions of the buried fluorophore in small animals and diagnose the early cancer. For the purpose of improving the performance of the reconstructed image, simplified spherical harmonics approximation (SPN) based on the radiative transport equation (RTE)is proposed to perform the forward simulation. To overcome the influence of ill-posedness and receive a more accurate reconstructed image, the Laplace regularization method is introduced to reconstruct the inverse problem. Numerical experiments reveal that the proposed method can acquire high-quality reconstructed images, especially of the small object and multi-objects.
To avoid the weakness that the sender can fully control the shared key alone in the Hsueh and Chen's two-party quantum key agreement (QKA) protocol with maximally entangled states, a possible solution is presented by adding the receiver's unitary operation. The unitary operation instead of the security checking is utilized, which makes this protocol fundamentally meet the basic requirement that in a quantum key agreement each participant equally contribute to the generation and distribution of the shared key. Therefore the security against the participant attack is based on basic physical principles rather than on the checking photons technique. Security analysis shows that this protocol is secure against the outside attack and participant attack. Compared with the previous improved protocol, the weakness is avoided with less qubits and the efficiency of the protocol is improved.
Because in the unknown complex battlefield environment, there may be multiple illuminators around the receiver, the basic information on the illuminator is unknown, and it is impossible to distinguish between interested and interfering signals, so that it is impossible to obtain accurate direction information on the interested station, we propose a cyclostianarity-based direction of arrival estimation method. First, for unknown cyclostiaonarity in the passive bistatic radar, we propose to use the cyclic autocorrelation function of the received signal to obtain cycle-frequency information on each base station signals. Then the cyclostianarity of the signal of interest is applied to enhance the signal of interest, while suppressing other clutters. Finally, the simulation method verifies that the proposed method can obtain more accurate direction estimation than the conventional method, and that it is also applicable to the underdetermined case where the number of antennas is less than the number of sources.
Aiming at the problem of weights decision of green-assessment-indexes, a new method based on the analytic network process (ANP) and theory of life cycle assessment (LCA) is proposed to compute the assessment indexes' weights. Firstly, the assessment indexes in life cycles of a product are presented. Secondly, according to the correlations among different indexes in the same hierarchy, the weights of green-assessment-indexes in different life cycles of a product are decided by the ANP. The results indicate that the analysis by the proposed method is more comprehensive and objective than that by the AHP alone.
In order to solve the problem that the direct matrix inverse(DMI) algorithm for clutter suppression can not be real-time processing in the passive radar engineering application, a segmented parallel DMI algorithm(called P-DMI) is proposed. By considering the feature of the DMI algorithm, the entire operation block is broken up into several identical sub-blocks, and in the Compute Unified Device Architecture, these sub-blocks are processed in parallel to achieve the purpose of improving the processing efficiency. Experimental results indicate that this algorithm's computation efficiency is raised more than 25 times compared with the traditional serial algorithm when the sampling rate is 200kHz and the clutter cancelation order is equal to 128. Also, the method has been used in real-time signal processing for passive radar successfully.
The rubidium atomic clock is most commonly used. The traditional circuit scheme usually adopts the comparison of the same frequency signals as a closing loop. Due to the existence of many frequency multipliers, the short stability of the rubidium clock is changing. Based on the principle of phase group synchronization and phase group continuation, the construction of the clock is improved by the frequency link in the generalized phase processing. The frequency link method in the generalized phase processing is spreading into the phase measurement between different frequency signals. Compared with the traditional method, the scheme simplifies the frequency transforming circuit and decreases the phase noise from them. With the simple construction the phase group synchronization improves the stability and reduces the phase noise.
With the density of network-on-chip(NoC) integration getting higher, the low-power mapping has become a hotspot research. A novel shuffled frog-leaping algorithm(SFLA) is used for solving the NoC mapping problem based on the concept of adjustment sequence. To further enhance searching capability, the proposed SFLA is improved with the adaptive chaos tactic and strategy of multi-neighborhood annealing. Experimental results shows that the improved SFLA has the advantage over the SFLA and annealing SFLA of better optimizing performance, thus reducing the communication power further.
Based on the maximum independent set and first-fit algorithm, we design a data aggregation algorithm, Peony-tree-based Data Aggregation (PDA). On the basis of the PDA, using the time-division multiplexing method, we introduce the concept of low-power sleep schedule in the cyclical time slot of data aggregation. It is largely possible to reduce the amount of data transmission,network time delay and achieve low-power data aggregation. Simulation results show that the proposed algorithm can reduce network energy consumption, prolong the network lifetime and reduce the network delay cost.
A novel ultra-thin dual-band metamaterial absorber is designed. Its absorbing mechanism is illuminated by calculating the effective impedance and analyzing the electric fields as well as currents distributions. Then the absorber is applied to the dual-band microstrip antenna to reduce its in-band RCS (Radar Cross Section). The results show that this absorber achieves high absorption in two frequency bands. Moreover, its absorbing properties are incident angle insensitivity and polarization independence, and when it is loaded to the dual-band microstrip antenna, it can reduce the antenna's RCS by 8.59dB and 9.9dB at 4.29GHz and 6.49GHz, respectively, which are the working frequencies of the dual-band antenna. There is a good agreement between simulated and measured results, showing that this absorber can be used for the improvement of the dual-band antenna's in-band invisibility of the antenna.
According to the measurement noise feature of the GPS receiver and the degeneracy phenomenon and for alleviating the sample impoverishment problem in the particle filter (PF), the GPS receiver autonomous integrity monitoring (RAIM) method based on an algorithm combining the genetic resampling particle filter with the likelihood ratio is presented. By setting up the test statistic of satellite fault detection, satellite fault detection is undertaken by checking the cumulative log-likelihood ratio (LLR) of system states. The selection, crossover and mutation of the genetic algorithm are melted into the particle filter, the accuracy of the particle filter is improved, and the genetic of particles is manipulated in the real domain. However, the coding of genetic manipulation is avoided. Simulation results demonstrate that the proposed algorithm can effectively detect and isolate fault satellite and improve the detection performance under conditions of non-Gaussian measurement noise. Therefore, the feasibility and validity of the proposed algorithm for RAIM are verified.
In order to solve the problems of high communication overhead and computational complexity for reconstructing the sparse frequency spectrum in conventional cooperative wideband spectrum sensing, a novel decentralized algorithm based on distributed subspace estimation is proposed. In the proposed method, the subspace is estimated directly from the sub-Nyquist samples and then the orthogonality property of the signal subspace and noise subspace can be exploited to complete spectrum sensing. To obtain the spatial diversity gain, the global signal subspace is estimated by using the distributed algorithm based on the diffusion adaptation cooperation scheme. Theoretical analysis and simulation results show that the method does not reconstruct the original signal spectrum, with lower computational complexity. The fully distributed cooperative scheme improves the performance of spectrum sensing and has a lower communication amount.
A novel image enhancement algorithm based on estimating the upper and lower boundary is presented. The method employs the upper and lower boundary to adjust the image details adaptively and dehaze the image, respectively and control the extent of image enhancement flexibly by adjusting the distance between the upper and lower boundary. The weighted median filter is adopted to calculate the upper and lower boundary for preserving image edges. Simulation results show that the proposed algorithm can improve the visual quality of the image efficiently, preserve the details, compress the high dynamic range, reduce halo artifacts and make the image more realistic and natural.
Based on the centralized control plane in SDN, an online traffic anomaly detection method (OpenTAD) is proposed. Firstly the flow table statistic is collected from the controller online, and the traffic matrix and sample entropy matrix are constructed and assembled. Then the PCA method is used to detect the abnormal traffic. The result of experiments show that, compared with the traditional PCA method which disposes the traffic matrix or the entropy matrix respectively offline, the OpenTAD is simple and effective, and traffic anomaly could be isolated rapidly. This method is a lightweight online traffic anomaly detection method for SDN.
Considering the low service availability and limited usage scenarios of state modeling for the single-satellite system, the state modeling of the Land Mobile Satellite (LMS) channel, based on the model parameters extracted from the Global Navigation Satellite Systems(GNSS) measurement data, is analyzed for much more scenarios. A joint generation of the states sequence for the dual-satellite is presented by the first-order Markov chain and semi-Markov chain. Various elevation combinations and azimuth separations in terms of correlation coefficients, state probabilities, and state duration statistics are analyzed. Simulation results show that the semi-Markov model with lognormal-fit can describe the state modeling of the dual-satellite propagation channel more accurately and effectively compared with the measurements. It has better applicability for various constellations in different channel environments, and can be used in modeling of the multi-satellite channel and system performance analysis.
The Steered Response Power(SRP)-based acoustic source localization algorithm with microphone arrays has been shown to be robust in noisy and reverberant environments. However, grid-search methods used to find a global maximum of the SRP image are computationally-intensive. In this paper, we propose a different strategy where, instead of the SRP at discrete spatial positions, the average of multiple Cross-Correlation(CC) values is evaluated as a cost function. The multi-stage region contraction is then used to find the maximum of the cost function to reduce the computational burden. The determination of CC accumulation limits does not increase the amount of calculation significantly. For incorporating additional spatial knowledge at each search grid, the proposed algorithm allows for a coarser spatial grid and reduces the computational cost with almost no loss of accuracy. Experiments carried out under different acoustic conditions confirm the validity of the proposed approach.
A detection and parameter estimation method based on expanded Wigner-Hough transform(WHT) is proposed to solve the detection and parameter estimation problem of the polyphase code signal in a low SNR. The polyphase code signal exhibits the characteristics of parallel multi-ridges in Wigner-Ville distribution(WVD). According to the characteristics, the expanded WHT uses the improved kernel function to cumulate the energy of polyphase code signal parallel multi-ridges in WVD. It can complete the signal detection and estimate the signal's modulation parameter. Theoretical analysis and simulation both indicate that the expanded WHT can accomplish the detection and parameter estimation of the polyphase coded signal in a low SNR, and is not affected by the coding type.
A proximate time-optimal control (PTOC) scheme with mode switching is proposed for typical servo systems characterized by the double-integrator model, aiming to achieve fast and accurate position regulation under speed constraint. The PTOC law exerts the maximum control authority for acceleration and deceleration when the initial position error is large, and ensures a smooth transition to linear control when the error goes down to some specified value. To satisfy the speed constraint, a stage for speed regulation is inserted between the acceleration stage and the deceleration stage of the servo system, and a mode-switching logic is designed. A linear extended state observer is adopted to estimate the un-measured speed and the unknown disturbance, to be used for feedback and compensation, so as to remove the steady-state error. The control scheme is then applied to a permanent magnet synchronous motor (PMSM) position servo system. Experimental tests have been carried out using the TMS320F2812DSP and the results verify that the controlled system is capable of tracking a wide range of target positions with desirable performance in the presence of load disturbance and speed constraint.
Change detection for SAR images can be transformed into the clustering for the difference image of SAR images. Since SAR images have speckle noise, a new adaptive particle swarm clustering algorithm using neighborhood information is proposed for improving the clustering results. The degrees of membership of the neighbors around each central pixel are introduced into the new objective function based on the fuzzy c-means (FCM) clustering algorithm, and the centers of clusters are optimized by the global searching of adaptive particle swarm. By the self-study operator of the proposed method, the degree of membership of each pixel can be revised based on the degrees of membership of all the neighboring pixels. Experimental results show that the proposed method is less sensitive to noise than the FCM and quantum-inspired immune clonal clustering algorithm by reason of using neighborhood information, and is better than the fuzzy local information c-means clustering algorithm on image detail preservation and run time.
To overcome computational redundancy and memory-access redundancy of the traditional GPU-accelerated CPML technique, a novel division-free and minimum-access CPML scheme is proposed. In the proposed scheme, the division operators in the CPML method are merged into a series of fixed coefficients by optimally rearranging the iteration process of CPML and then, the reduplicate memory accesses are eliminated by updating the FDTD and CPML operation in the PML region jointly. Experimental results show that the proposed structure can save up to 70% operation time compared with the traditional GPU-CPML technique and 44% of field updating in the PML region, without any loss of accuracy.
For the large bandwidth, high sampling rate, high storage capacity in linear frequency modulated(LFM) signals applied in wideband radar, this paper designs an overall solution for undersampling the radar echo of LFM signals based on compressive sensing(CS). First, by use of the good energy characteristics of LFM signals in the fractional Fourier transform(FRFT) domain, a novel orthogonal base dictionary based on the DFRFT nuclear matrix is proposed. Combining this dictionary with random demodulation and matching pursuit algorithms, an LFM radar echo signal sampling and reconstruction system model is built. Simulation results verify the feasibility and effectiveness of this scheme, and sparse representation of the LFM radar echo in the orthogonal basis dictionary is superior to the existing waveform matching dictionary, and has better anti-noise and adaptive performance.
Aimed at the fact that predistortion can not cancel the nonlinear interference and memory interference which are caused by the power amplifier in the satellite and the high order modulation of the signal, a post nonlinear interference cancellation algorithm is proposed. Based on the fact that the high order signal under the DVB-S2 has the multiple amplitude, and combined with the memory of the amplifier, the algorithm builds an adaptive nonlinear interference cancellation module to realize the linearization of the satellite's output signal. The algorithm can be used by high order modulation and it can remove the nonlinear effect of the satellite's power amplifier perfectly. Simulation results about the bit error radio, power spectrum power and constellation show that our proposed algorithm can eliminate the nonlinear and memory interference.
The large-scale MIMO system using the regularized zero-forcing (RZF) precoding is considered and the space degree of freedom (DOF) is introduced. The expression for the approximate ergodic capacity is derived and the problem of the joint RZF precoding and user number optimization is presented. Theoretical analysis illustrates that the joint optimization problem can be transformed to the user number optimization problem under some conditions. It can be derived that the unique optimum solution can be obtained by using a bisection based joint optimal algorithm. Simulation results show that the proposed algorithm can achieve almost the same capacity as the best optimization algorithm but with a much lower complexity in the large-scale MIMO systems.
To address the energy dispersion problem caused by the long time signal combination for high dynamic receivers, a new Doppler shift acquisition algorithm based on the iterative searching range correction (SRC) is proposed. Considering the received signal's continuity property, first, the single SRC algorithm uses the two Doppler estimation results obtained in the previous two combination periods to correct the third combination period's searching range for the third estimation result and analyzes the influence of the searching range's size on acquisition probability, and then, iterative SRC algorithm adopts cascaded multiple single SRCs to gradually narrow the Doppler searching range, thus increasing the Doppler acquisition performance furthermore with an upper bound on the acquisition probability with the iterations. Effectiveness of this proposed algorithm is verified by simulation results.
Diversity among individuals and accuracy of individuals are two important factors to decide the ensemble generalization error, whereas enhancing diversity is at the cost of decreasing the accuracy of individuals. Hence, in order to improve the performance of radar target recognition classified by a single classifier, this paper introduces a new radar target recognition method based on the integer matrix linear transformation selective classifier ensemble that considers the balance of diversity and accuracy. Firstly, in order to enhance the diversity, the individual classifiers are considered as original targets of the linear transformation, and instead of the mean value of samples, the true labels are considered to construct an integer matrix. By projecting individual classifiers on the lines through the true labels, a set of new classifiers is obtained based on the project transformation. Secondly, according to two rules that measuring the performance of the classifier, the accuracy rate and RPF-measure, some new classifiers that can obtain better performance are selected to ensemble for increasing the accuracy of classifiers of an ensemble. Finally, the performance of radar target recognition is improved by combining the selected new classifiers. Experimental results of UCI datasets and the radar range profile indicate that the proposed method balances effectively diversity and accuracy, and that it can obtain better performance for radar target recognition compared with single classifier algorithms and other methods.
In the presence of false-target deception jamming, the anti-jamming ability of monostatic radar is limited, and anti-jamming methods based on data fusion cannot fully exhaust the anti-jamming ability of netted radar due to the high information loss rate at the data level. Echoes of true targets are essentially independent, when they are received by node radars from sufficiently different directions due to the fluctuations of target radar cross section (RCS). However, deception jamming signals received from different directions would be highly coherent. Exploiting this difference, an active false-target discrimination method for netted radar based on target spatial scattering characteristics is proposed, in which a correlation test is implemented between slow-time complex envelope sequences of different targets to discriminate active false-targets. Simulation results indicate that the approach proposed can effectively discriminate false-targets and ensure the recognition probability of true targets.
Due to the problem of high grating-lobe caused by phase discontinuity for frequency bandwidth synthetic, a new method of frequency synthetic bandwidth is proposed. The cause for phase discontinuity of frequency spectrum is the relative motion between radar and scatterers. The phase error for every sub-pulse according to different forms of the slant range between radar and scatterers is compensated by this method. A new approach is put forward for step frequency signal processing after the frequency band is synthesized. First, the pulse is compressed and frequency band is synthesized. After the frequency band is synthesized, the second range compression and the range migration correction are implemented. Then, phase discontinuity due to the corrected range migration correction is avoided. Finally, Chirp Scaling is applied to obtain the squint two-dimension high resolution SAR (Synthetic Aperture Radar, SAR) image. In order to identify the availability of this method, simulation results are shown in the paper. Experiments on raw data and simulation show that the wide-band signal could be synthesized by the narrow-band stepped signal.
