Null Algorithm Research Articles

Elevation Estimation Algorithm for Low-Altitude Targets in Multipath Environment

The algorithm proposed in this study estimates the multipath elevation of targets at low altitudes, including near-zero elevation. Although the double null algorithm is a maximum likelihood elevation estimation algorithm, it diverges when the target elevation is near zero. Addressing this issue, the selective double null algorithm improves the accuracy of multipath elevation at low altitudes by applying previously measured antenna near-field patterns. However, it cannot be applied to active electronically scanned array radars, since antenna beam patterns vary with the steered azimuth and elevation angles. In this paper, the proposed algorithm modifies the double null algorithm to estimate the elevation in the divergence state more accurately. Since it is based on the multipath energy function, the antenna near-field pattern is unnecessary. In addition, to increase the accuracy of elevation estimation, an operation method that selectively uses the estimated elevations according to several conditions is proposed. The proposed algorithm was verified through simulations.

Towards 5G Security Analysis against Null Security Algorithms Used in Normal Communication

mailto: 5G network makes our lives delicate and more pleasant, and its security will impact the operation of the entire society. Compared with the LTE network, 5G brings up many new security features and possesses more sophisticated and robust security mechanisms, while there are still many potential security issues with the 5G network. Therefore, the security analysis of the 5G network is highly crucial. Null security algorithm (i.e., NEA0 and NIA0) is used in normal communication, a security vulnerability that exists and has not been fully addressed in the LTE network, but in the 5G network, no studies have been performed to demonstrate whether this security vulnerability still exists so far. Therefore, in this paper, we apply a systematic approach based on the principle of model checking to verify. We conduct an in-depth analysis of the signaling interaction and security mechanism for the attach procedure in the 5G network. And then, we model UE and AMF into two synchronous communication finite-state machines, extract the desired properties from 3GPP relevant specifications, and construct an adversary model to test the system’s security. By observing the operation of state machines and analyzing relevant protocol behavior, we discover that faulty security algorithm selection could result in the acceptance of the null security algorithm (i.e., NEA0 and NIA0) on the side of the core network, and attackers can exploit this to trigger IP spoofing attacks and SUPI catching attacks on the victim UE. We analyze the root cause of these network attacks and propose an anomaly detection method to avoid these network attacks from being launched effectively.

Radiator threat evaluation with missing data based on improved technique for order preference by similarity to ideal solution

To solve the problem of the missing data of radiator during the aerial war, and to address the problem that traditional algorithms rely on prior knowledge and specialized systems too much, an algorithm for radiator threat evaluation with missing data based on improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been proposed. The null estimation algorithm based on Induced Ordered Weighted Averaging (IOWA) is adopted to calculate the aggregate value for predicting missing data. The attribute reduction is realized by using the Rough Sets (RS) theory, and the attribute weights are reasonably allocated with the theory of Shapley. Threat degrees can be achieved through quantization and ranking of radiators by constructing a TOPSIS decision space. Experiment results show that this algorithm can solve the incompleteness of radiator threat evaluation, and the ranking result is in line with the actual situation. Moreover, the proposed algorithm is highly automated and does not rely on prior knowledge and expert systems.

Fast Thresholding Algorithms with Feedbacks and Partially Known Support for Compressed Sensing

Some works in modified compressive sensing (CS) show that reconstruction of sparse signals can obtain better results than traditional CS using the partially known support. In this paper, we extend the idea of these works to the null space tuning algorithm with hard thresholding, feedbacks ([Formula: see text]) and derive sufficient conditions for robust sparse signal recovery. The theoretical analysis shows that including prior information of partially known support relaxes the preconditioned restricted isometry property condition comparing with the [Formula: see text]. Numerical experiments demonstrate that the modification improves the performance of the NST+HT+FB, thereby requiring fewer samples to obtain an approximate reconstruction. Meanwhile, a systemic comparison with different methods based on partially known support is shown.

Phase analysis and error compensation of anti-jamming nulling algorithm for satellite navigation array antenna

The traditional adaptive nulling antenna array anti-interference algorithm can cause phase distortion, make the antenna phase unstable, and produce positioning error. Based on the analysis of the adaptive nulling antenna array anti-jamming algorithm, this article deduces the calculation method of its phase centre and the stage of real-time change, determines the phase centre error, and calculates the compensation value which can be used for the repositioning after correction. Simulation and experimental results verify the rationality and effectiveness of the algorithm, which can be used to improve the positioning accuracy of anti-jamming array antenna GNSS receiver.

Phase analysis and error compensation of anti-jamming nulling algorithm for satellite navigation array antenna

Phase analysis and error compensation of anti-jamming nulling algorithm for satellite navigation array antenna

THINNING A SUBSET OF SELECTED ELEMENTS FOR NULL STEERING USING BINARY GENETIC ALGORITHM

THINNING A SUBSET OF SELECTED ELEMENTS FOR NULL STEERING USING BINARY GENETIC ALGORITHM

Adaptive interference nulling with pattern maintaining under mainlobe subspace and quadratic constraints

A fast adaptive interference nulling algorithm with arbitrary pattern maintaining without direction of arrival is proposed under the framework of generalised sidelobe canceller (GSC). The problem is formulated to optimise the weight by minimising the total output power of the beamformer, while keeping the antenna gain accurately approximated to that of the quiescent pattern by the mainlobe subspace constraint (MSC) and the weight quadratic constraint. The MSC is constructed by the dominant eigenvectors of the mainlobe covariance matrix. The closed-form solution to this problem is obtained by two steps. First, the quadratic constraint is relaxed to obtain the weight in the form of a GSC beamformer with diagonal loading (DL) sample covariance matrix. Then, the stringent quadratic constraint is guaranteed by optimising the DL level, which is precisely estimated by a simple iterative equation. The maintenance of pattern mainlobe and the reduction of the computation complexity can be achieved simultaneously. Numerical experiments are performed to demonstrate the effectiveness and efficiency of the proposed algorithm, and discuss the influence of mutual coupling between antenna elements.

Modified Neutral Models as Benchmarks to Evaluate the Dynamics of Land System (DLS) Model Performance

Assessing model performance is a continuous challenge for modelers of land use change. Comparing land use models with two neutral models, including the random constraint match model (RCM) and growing cluster model (GrC) that consider the initial land use patterns using a variety of evaluation metrics, provides a new way to evaluate the accuracy of land use models. However, using only two neutral models is not robust enough for reference maps. A modified neutral model that combines a density-based point pattern analysis and a null neutral model algorithm is introduced. In this case, the modified neutral model generates twenty different spatial pattern results using a random algorithm and mid-point displacement algorithm, respectively. The random algorithm-based modified neutral model (Random_MNM) results decrease regularly with the fragmentation degree from 0 to 1, while the mid-point displacement algorithm-based modified neutral model (MPD_MNM) results decrease in a fluctuating manner with the fragmentation degree. Using the modified neutral model results as benchmarks, a new proposed land use model, the Dynamics of Land System (DLS) model, for Jilin Province of China from 2003 to 2013 is assessed using the Kappa statistic and Kappain-out statistic for simulation accuracy. The results show that the DLS model output presents higher Kappa and Kappain-out values than all the twenty neutral model results. The map comparison results indicate that the DLS model could simulate land use change more accurately compared to the Random_MNM and MPD_MNM. However, the amount and spatial allocation of land transitions for the DLS model are lower than the actual land use change. Improving the accuracy of the land use transition allocations in the DLS model requires further investigation.

단일포트 위상배열안테나에서 주빔 왜곡 현상을 줄이기 위한 적응형 널링 알고리즘

단일포트 위상배열안테나에서 주빔 왜곡 현상을 줄이기 위한 적응형 널링 알고리즘

이동형 재밍환경에서 널 합성을 위한 적응형 널링 알고리즘

본 논문에서는 단일포트시스템으로 설계된 배열안테나에서 재밍신호나 간섭신호 방향으로 방사패턴에 널(null)을 형성하는 적응 알고리즘을 제안한다. 제안한 적응 알고리즘은 재밍신호나 간섭신호의 크기나 입사방향에 대한 사전정보를 요구하지 않으며, 배열안테나의 일부 RF 경로의 위상을 제어하는 부분적응(partially adaptive) 알고리즘이다. 제안한 적응 알고리즘은 최적화 알고리즘의 한 종류인 PSO(Particle Swam Optimization) 알고리즘과 gradient-based 섭동 적응 알고리즘을 혼합하여 시간에 따라 간섭신호의 입사방향이 변화하는 이동형 재밍환경에서도 적응적으로 안정적인 널링 성능을 가진다. In this paper, an adaptive nulling algorithm which can be used to form nulls in the direction of jammer or interference signals in array antennas of single port system is proposed. The proposed adaptive algorithm does not require a priori knowledge of the incoming signal direction and can be applied to the partially adaptive arrays. This algorithm is the combination of the PSO(Particle Swam Optimization) algorithm and the gradient-based perturbation adaptive algorithm, which shows stable nulling performance adaptively even on the moving jammer environment where the incident direction of the interference signal is changing with time.

양자화 진화알고리즘을 적용한 널 패턴합성 알고리즘의 특성 연구

양자화 진화알고리즘을 적용한 널 패턴합성 알고리즘의 특성 연구

Multi-resolution intrusion localization algorithm through cepstrum in distributed fiber optic Sagnac interferometer

Distributed fiber optic sensors are studied extensively, for monitoring abnormal events in continuous space, due to the advantages of immunity to electrical interference, non-conductivity and light weight. Moreover, the position of abnormal events, such as intrusions, could be determined directly without additional measurements. Among the various techniques, Sagnac interferometers prove to be promising for providing high sensitivity and large dynamic range in detecting intrusions. Two interference light beams are used which are naturally of equal optical path length in static status. When an intrusion occurs along the sensing fiber, the two light beams arrive at the intrusion position in different time and thus cause different phase changes induced by the intrusion. Analysis of the phase difference signal can predict the intrusion position, as well as the existence of the intrusion. As a Faraday rotator mirror (FRM) connected in the far-end of sensing fiber, both beams travel twice to the intrusion position after being reflected by the FRM. The propagation time interval T between the two interactions corresponds to the distance between the intrusion position and the far-end of sensing fiber Lx, which is further extracted as the localization of intrusion. Previously, the auto-correlation algorithm deals with the phase difference signal in the time domain and the null-frequency algorithm is used in frequency domain to calculate the distance. However the poor localization performance usually can not meet the requirement in high-quality monitoring applications. To determine the position of an intrusion effectively and accurately, the localization algorithm which deals with the phase difference signal in cepstrum domain is proposed in this article. Inspired by the research on the pitch examination we first introduce the algorithm for intrusion localization. Through theoretical analysis, the phase difference signal can be regarded as the convolution of the original waveform of intrusion and the T-related transform function. By applying the fast Fourier transform to the logarithmic spectrum, the phase difference signal is changed into the cepstrum domain, where the original waveform of intrusion and the transform function behave differently and are separated. The propagation time interval T, as well as the distance Lx, can be directly acquired from the peak produced by the transform function. In addition, to overcome the roughness in localization resolution brought by down-sampling of the phase difference signal, the decimator factor is scanned from 30 to 50 for multi-resolution localization at an original sampling rate 4 million/s-1. Besides the basic peak, high order peaks also emerge in the cepstrum in high signal-noise-ratio condition, which can also be used for localization. Since the localizations from different decimator factor and different peaks spread around the actual distance, an average of all reasonable localizations is calculated as the ultimate localization result for the intrusion. Firstly in experiments, intrusions occurring at a position 40.498 km are produced for the verification of the algorithm. The localizations are 40.489, 40.515 and 40.487 km, with localization errors as small as 9, 17 and 11 m respectively. Intrusions at different positions are tested and also correctly localized. For comparison, the standard deviations of localization error are respectively 695 m and 118 m for the auto-correlation algorithm and the null frequency algorithm, which are 58 times and 10 times of the result 12 m, which is obtained by the proposed cepstrum algorithm. The performance suggests promise to achieve better localization in practical applications.

Fast Adaptive Beamforming with Smart Antenna for Radio Frequency Repeater

We present a fast adaptive beamforming null algorithm with smart antenna for Radio Frequency Repeater (RFR). The smart antenna system is realized by a Direction Of Arrival (DOA) Estimator, whose output is used by an adaptive beamforming algorithm to shape a suitable radiation pattern of the equivalent antenna; so that the co-channel interference due to retransmitting antenna can be reduced. The proposed adaptive beamforming algorithm, which has been proved by formulaic analysis and simulation, has a lower computation complexity yet better performance.

An Anti-jamming Algorithm for Attitude Measurement Based on Antenna Array

Aiming at the problems existing in the attitude measurement using carrier phase of navigation signal in the jamming environment, an antenna array for anti-jamming attitude measurement is constructed. The antenna array is constructed by three circle array with core. An anti-jamming measurement method based on antenna array is proposed. This method uses array antenna to estimate the direction of arrival jamming signal though MUSIC algorithm. Then the adaptive nulling algorithm based on the linear constrained minimum variance algorithm is used to eliminate the jamming and hold the navigation signal. Finally, the double difference method is used to measure the attitude. The whole attitude information is obtained by the attitude measurement of the two baselines. Simulation has been made for eliminating the jamming with adaptive nulling algorithm. Comparison of the attitude measurement accuracy is also made by simulation. The results show that the algorithm we proposed can significantly inhibit the jamming and improve the accuracy of attitude measurement.

Blind Equalization in OFDM Systems by Channel Shortening and Channel Diversity Exploitation

We propose two alternative approaches for blind channel shortening to design time domain finite impulse response equalizer (TDE) in multicarrier single input, multiple output systems. The first approach we utilize the constant envelop of the transmitted signal called constant modulus (CM). Second approach is based on decision directed algorithm, where we update time domain equalizer using decision directed cost function. These cost function have been widely studied for single carrier systems, implementing them in multicarrier scenario is of great importance. Simulations shows they outperform classical multicarrier equalization by restoration of redundancy (MERRY) and Carrier nulling algorithm (CNA) that utilizes redundancies inherent in carriers in terms of bit error rate. General Terms Channel equalization algorithms in wireless communication.

Research on Voltage Fluctuation and Flicker Extraction Method Based on Null Space Pursuit Algorithm

In order to obtain more accurate and rapid voltage fluctuations and flicker signal and provide fast and accurate data for power quality analysis and improvement, this paper proposes the improvement measures of null space pursuit algorithm based on the analysis of the principle of null space pursuit algorithm, which improves the value of practical application. By the simulation analysis, it proves that the combined null space pursuit algorithm not only has the same advantage of high precision extraction and decent noise reduction capabilities as original algorithm but also improves its computing speed and enhances its practical value.

Blind focusing algorithm applied to the acoustic signal of a maneuvering rotorcraft

An algorithm was developed and tested to blindly focus the acoustic spectra of a rotorcraft that was blurred by time-varying Doppler shifts and other effects such atmospheric distortion. First, the fundamental frequency generated by the main rotor blades of a rotorcraft was tracked using a fixed-lag smoother. Then, the frequency estimates were used to resample the data using interpolation. Next, the motion-compensated data were further focused using a technique based upon the phase gradient autofocus (PGA) algorithm. The performance of the algorithm was evaluated by analyzing the increase in the amplitude of the harmonics due to focusing the data. For most of the data, the algorithm focused the harmonics between approximately 10-90 Hz to within 1-2 dB of an estimated upper bound (UB) obtained from conservation of energy and estimates of the Doppler shift. In addition, the algorithm was able to separate two closely spaced frequencies in the spectra of the rotorcraft. The algorithm developed can be used to preprocess data for classification, nulling, and tracking algorithms.

다중경로 환경에서 다중빔 탐색레이더에 적용 가능한 표적 고각오차 혼성 보정 기법

The multibeam surveillance radar is a state-of-art of 3D radar technology. It applies the stacked beams realized by a digital beamformer. In this paper, a hybrid compensation technique on elevation angle errors for low elevation angle targets over the sea in multipath radar environments is proposed. The proposed method can be applied to stacked beam radars. Double null algorithm based on maximum likelihood method in 3-D beamspace domain works well unless the phase difference between the two rays(direct and specular path) is close to 0° and the magnitude of reflection coefficient is close to 0. To overcome these problems, we propose a hybrid compensation technique which uses the selective double null algorithm and the beam-ratio compensation technique for low-elevation errors on a log scale. Results of computer simulation show that the proposed method outperform conventional monopulse method and double null algorithm only under various multipath environments.Keywords : Mutibeam Surveillance Radar(다중빔 탐색 레이더), Digital Beamformer(디지털 빔형성기), Multipath(다중경로), Monopulse(모노펄스)

Distributed Sum-Rate Optimization for Full-Duplex MIMO System Under Limited Dynamic Range

Distributed sum-rate-maximizing covariance matrices design for full-duplex multi-input multi-output communication is considered, where the information of the loopback interference channels cannot be exchanged reliably due to their large dynamic ranges. We propose a structured covariance matrices design which finds the optimal balance between the two solutions in the extremes of the weak and strong self-interference through a single-parameter optimization. We further propose a low-complexity null projection matrix design algorithm, in which the solution in the strong self-interference regime is designed in the sense to maximize the received channel gain. Exploiting the well-posed structure, the proposed scheme nearly achieves the sum-rate of the previous scheme based on the gradient projection with significantly less amount of inter-node iterations, yielding an increased effective sum-rate and reduced overall complexity for the practial channel block lengths.