Modeling Target Detection and Performance Analysis of Electronic Countermeasures for Phased Radar

Interference is a key factor in radar return misdetection.Strong interference might make it difficult to detect the signal or targets.When interference occurs in the sidelobes of the antenna pattern,Sidelobe Cancellation(SLC)and Sidelobe Blanking are two unique solutions to solve this problem(SLB).Aside from this approach,the probability of false alert and likelihood of detection are the most essential parameters in radar.The chance of a false alarm for any radar system should be minimal,and as a result,the probability of detection should be high.There are several interference cancellation strategies in the literature that are used to sustain consistent false alarms regardless of the clutter environment.With the necessity for interference cancellation methods and the constant false alarm rate(CFAR),the Maisel SLC algorithm has been modified to create a new algorithm for recognizing targets in the presence of severe interference.The received radar returns and interference are simulated as non-stationary in this approach,and side-lobe interference is cancelled using an adaptive algorithm.By comparing the performance of adaptive algorithms,simulation results are shown.In a severe clutter situation,the simulation results demonstrate a considerable increase in target recognition and signal to noise ratio when compared to the previous technique.

ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

With the increasing number of switches in Software-Defined Network-ing(SDN),there are more and more faults rising in the data plane.However,due to the existence of link redundancy and multi-path forwarding mechanisms,these problems cannot be detected in time.The current faulty path detection mechan-isms have problems such as the large scale of detection and low efficiency,which is difficult to meet the requirements of efficient faulty path detection in large-scale SDN.Concerning this issue,we propose an efficient network path fault testing model ProbD based on probability detection.This model achieves a high prob-ability of detecting arbitrary path fault in the form of small-scale random sam-pling.Under a certain path fault rate,ProbD obtains the curve of sample size and probability of detecting arbitrary path fault by randomly sampling network paths several times.After a small number of experiments,the ProbD model can cor-rectly estimate the path fault rate of the network and calculate the total number of paths that need to be detected according to the different probability of detecting arbitrary path fault and the path fault rate of the network.Thefinal experimental results show that,compared with the full path coverage test,the ProbD model based on probability detection can achieve efficient network testing with less overhead.Besides,the larger the network scale is,the more overhead will be saved.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

MAPOD Analysis in Eddy Current Testing of Flaws Considering Multiple Response Signals and Multiple Flaw Parameters

The reliability of the eddy current testing (ECT) in flaw detection is quantitatively evaluated by theprobability of detection (POD). Precise and efficient modeling of POD gives direction for the implement of ECTon sites to avoid false or missing flaw detection. Traditional POD analysis focuses on single uncertain factor orsingle response signal with limited credibility in engineering. This paper considers multiple response signals andmultiple flaw parameters to perform POD. The flaw length, the flaw depth, the coil impedance, and the magneticflux density are comprehensively studied under various lift-off distances. A finite element model (FEM) of ECT isestablished and verified with experiments to obtain sufficient simulation data for discrete POD modeling. Thecontinuous POD function is then fitted based on the discrete values to show the superiority of integrating multiplefactors. A comparison with conventional POD analysis further demonstrates the higher reliability of ECT flawdetection considering multiple flaw parameters and multiple response signals, especially for small flaws.

Adaptive double-threshold energy detection algorithm for cognitive radio

Due to the fact that the conventional spectrum sensing algorithm is susceptible to noise, an adaptive double-threshold energy detection algorithm for a cognitive radio is proposed. Based on double-threshold energy detection, the algorithm can adaptively switch between one-round sensing and two-round sensing by comparing the observations with the pre-fixed thresholds. Mathematical expressions for the probability of detection, the probability of false alarm, and the sensing time are derived. The relationships including signal to noise ratio （SNR） vs. the probability of detection and SNR vs. the sensing time are plotted using Monte Carlo simulation and the algorithm is verified in a real cognitive system based on GNU Radio and universal software radio peripheral （USRP）. Simulation and experimental results show that, compared with the existing spectrum sensing method, the proposed algorithm can achieve a higher probability of detection within a reasonable sensing time.

Combining Radon-ambiguity transform with second-order difference to improve detection probability of LFM signals in low SNR

The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.

Study on the detection of the multiple unresloved targets

When the returns come from two or more unresolved targets (the signals are not resolved in the frequency or time domains) in a monopulse radar system, the direction-of-arrival (DOA)estimate indicated by the monopulse ratio is not the true information of the tracked target.Then the tracking systems is influenced. An approach has been proposed to detect whether the returns come from a single target or two unresolved targets. The above approach is extended from two to three unresolved targets. The simulation indicates that the detection probability under the three unresolved targets is not sure to exceed the detection probability under the two unresolved targets.

Hypothesis testing analysis and unknown parameter estimation of GPS signal detection

Hypothesis testing analysis and unknown parameter estimation of both the intermediate frequency(IF) and baseband GPS signal detection are given by using the generalized likelihood ratio test(GLRT) approach,applying the model of GPS signal in white Gaussian noise,It is proved that the test statistic follows central or noncentral F distribution,It is also pointed out that the test statistic is nearly identical to central or noncentral chi-squared distribution because the processing samples are large enough to be considered as infinite in GPS acquisition problem.It is also proved that the probability of false alarm,the probability of detection and the threshold are affected largely when the hypothesis testing refers to the full pseudorandom noise(PRN) code phase and Doppler frequency search space cells instead of each individual cell.The performance of the test statistic is also given with combining the noncoherent integration.

Estimation of Probability of Damage Detection in Offshore Structural Inspection

To characterize the uncertainty and fuzziness in offshore structural inspection, probability of detection (POD) must be determined. This paper presents the expressions for the POD of four different damage forms mainly existing in offshore structures. The fuzzy-set theory is applied to estimate human errors through the definition of inspection quality. Expressions of inspection quality are achieved. To verify the validity and correctness of the expressions, the data from an offshore platform field inspection of evaluation results of human errors affecting inspection quality are used to estimate the parameters of the POD. The results show that the present models can provide basis for further study of ofTshore structural inspection reliability.

Detection probability for six laser range-finders of the rotating rocket

To analyze factors that affect the detection probability of six laser range-finders of rotating rocket,taking a missile as the target,the detection model was established according to a detection mechanism.Based on the model,the detection probability was calculated via Monte Carlo method under different conditions.With the calculation results,the relationship of detection probability with the rolling rate and the missile velocity was illustrated in figures,when the laser emitting frequency was 10 kHz,20 kHz,30 kHz respectively under the condition that rocket met the front of missile as well as the condition that rocket met the rear of missile.The figures show that the detection probability increases as laser emitting frequency increases or the rolling rate increases,while it decreases as the missile velocity increases.Detection probability is higher when rocket meets the front of missile than that when rocket meets the rear of missile.In order to maintain a track of approaching Mach 2 targets,rotation rate should be more than 100 r/s.

Influence of Range Gate Width on Detection Probability and Ranging Accuracy of Single Photon Laser Altimetry Satellite

The influence of the single photon laser altimeter range-gate width on the detection probability and ranging accuracy is discussed and analyzed,according to the LiDAR equation,single photon detection equation and the Monte Carlo method to simulate the experiment.The simulated results show that the probability of detection is not affected by the range gate,while the probability of false alarm is relative to the gate width.When the gate width is 100 ns,the ranging accuracy can accord with the requirements of satellite laser altimeter.But when the range gate width exceeds 400 ns,ranging accuracy will decline sharply.The noise ratio will be more as long as the range gate to get larger,so the refined filtering algorithm during the data processing is important to extract the useful photons effectively.In order to ensure repeated observation of the same point for 25 times,we deduce the quantitative relation between the footprint size,footprint,and frequency repetition according to the parameters of ICESat-2.The related conclusions can provide some references for the design and the development of the domestic single photon laser altimetry satellite.

Mitigation of primary user emulation attack using a new energy detection method in cognitive radio networks

A most promising solution to the expansion of spectrum efficiency is cognitive radio(CR)and this expansion is achieved by permitting the licensed frequency bands to be accessed by unlicensed secondary users(SUs)with a lack of interference with licensed primary users(PUs).This utilization of CR networks in the spectrum sensing causes vulnerable attacks like primary user emulation(PUE)attack and here PUs play the role of malicious user and do not permit other users to utilize PUs channel even in their unavailability.On the basis of the traditional single-threshold energy detection algorithm,a novel modified double-threshold energy detector is formulated in the CR network and the detection probability,miss detection probability,probability of false alarm,and their inter-relationship are analyzed.This paper develops a modified double threshold energy detection cooperative spectrum sensing technique to alleviate the PUE attack.Finally,performance-based evaluation is carried out between the proposed and the existing energy detection spectrum sensing method that had no consideration on PUE attack.The resultant of the simulation in MATLAB has revealed that the proposed model has significantly mitigated PUE attack by means of providing outstanding performance.

Enhanced Intrusion Detection System for an EH IoT Architecture Using a Cooperative UAV Relay and Friendly UAV Jammer

In this paper,the detection capabilities and system performance of an energy harvesting(EH)Internet of Things(Io T)architecture in the presence of an unmanned aerial vehicle(UAV)eavesdropper(UE)are investigated.The communication protocol is divided into two phases.In the first phase,a UAV relay(UR)cooperates with a friendly UAV jammer(UJ)to detect the UE,and the UR and UJ harvest energy from a power beacon(PB).In the second phase,a ground base station(GBS)sends a confidential signal to the UR using non-orthogonal multiple access(NOMA);the UR then uses its harvested energy to forward this confidential signal to IoT destinations(IDs)using the decode-and-forward(DF)technique.Simultaneously,the UJ uses its harvested energy to emit an artificial signal to combat the detected UE.A closed-form expression for the probability of detecting the UE(the detection probability,DP)is derived to analyze the detection performance.Furthermore,the intercept probability(IP)and throughput of the considered IoT architecture are determined.Accordingly,we identify the optimal altitudes for the UR and UJ to enhance the system and secrecy performance.Monte Carlo simulations are employed to verify our approach.

Joint optimization algorithm of sensing thresholds and cooperative users in cooperative detection

Cooperative detection is an effective method to improve the spectrum sensing of Cognitive Radio (CR), and its detection performance can be improved through optimization. An optimization algorithm for cooperative detection based on "OR Rule" which can optimize the detection threshold of each user and the number of cooperative users simultaneously is proposed in this paper. The algorithm, which is based on minimizing the error detection probability, adopts partial fusion to improve the detection performance effectively. The simulation results show that the error detection probability of the proposed algorithm is lower than that of the cooperative detection algorithm with the settled threshold, and the better performance can be achieved through choosing fewer users.

Enhancing the Accuracy for Target Detection by Using Fast Orthogonal Search (FOS)

Target detection and bearing estimation are mainly obtained through spectral analysis of received signals. The detection performance of the periodogram and its variants methods is evaluated. The variants methods Performance evaluation through the Receiver Operating Characteristics （ROCs） are presented and compared from the viewpoint of probability of detection （Pd）, probability of false alarm （Pfa） by computer simulation. When the sinusoid frequency does not correspond to one of the spectral bins （mid-bin frequency situation）, the performance of all the mentioned detectors degrades. This research investigates the development of a bearing estimation method using Fast Orthogonal Search （FOS） to enhance spectral estimation which, improves both target detection and bearing estimation in case of low SNR inputs.

Detection Probability Analysis of Space-Based AIS Signal by Using Geometrical Model

To analyze the detection probability of shipbome AIS （automatic identification system） signal from space, a mathematical model dependent upon three factors of message collision avoidance, power of signal received by satellite and interference ratio of signal received is presented in the paper. The altitude and footprint area of the AIS satellite are discussed to overcome the collision of messages transmitted in the different time slots fxom different SOTDMA （self organizing time division multiple access） cell areas, but arrive at the same time slot due to the different signal path lengths. The simulated result shows that compared to the normal LEO （low ear~ orbit） satellite system, on average the maximum signal coverage area and the maximum FOV （field of view） of the AIS satellite system are reduced by 74% and 38%. The majority of power of signal transmitted fi＇om shipborne 12W-power AIS transmitters located within the maximum signal coverage area may be received with the sufficient margin of power of signal by the LEO satellite, but the space-based AIS system generally suffers from the insufficient CIR （carrier to co-channel interference ratio） of signal received since around 95% pairs of message simultaneously received by satellites may not be correctly decoded. The insufficient CIR of signal received is the bottleneck for the high message detection probability. Therefore, the measure of separating the collision messages should be further taken by the space-based AIS system to increase the detection probability.

A New Probability of Detection Model for Updating Crack Distribution of Offshore Structures

There exists model uncertainty of probability of detection for inspecting ship structures with nondestructive inspection techniques. Based on a comparison of several existing probability of detection (POD) models, a new probability of detection model is proposed for the updating of crack size distribution. Furthermore, the theoretical derivation shows that most existing probability of detection models are special cases of the new probability of detection model. The least square method is adopted for determining the values of parameters in the new POD model. This new model is also compared with other existing probability of detection models. The results indicate that the new probability of detection model can fit the inspection data better. This new probability of detection model is then applied to the analysis of the problem of crack size updating for offshore structures. The Bayesian updating method is used to analyze the effect of probability of detection models on the posterior distribution of a crack size. The results show that different probabilities of detection models generate different posterior distributions of a crack size for offshore structures.

Performance Analysis of Distributed Neyman-Pearson Detection Systems

The performance of a distributed Neyman-Pearson detection system is considered with the decision rules of the sensors given and the decisions from different sensors being mutually independent conditioned on both hypothese. To achieve the better performance at the fusion center for a general detection system of n 〉 3 sensor configuration, the necessary and sufficient conditions are derived by comparing the probability of detec- tion at the fusion center with that of each of the sensors, with the constraint that the probability of false alarm at the fusion center is equal to that of the sensor. The conditions are related with the performances of the sensors and using the results we can predict the performance at the fusion center of a distributed detection system and can choose appropriate sensors to construct efficient distributed detection systems.

Robust and Low-Complexity Synchronization for Energy Detection UWB Receiver

A simple method using aided sliding rectangular windows for synchronization in energy detector （ED） receiver is proposed for impulse-based ultra wideband radios （IR-UWB） under binary pulse position modulation （PPM）, therefore grants an attractive solution for gaining low complexity while the accompanying performance loss in terms of UWB signal reception is comparatively low. Also, a method is developed to sup- press noise through accumulation of integrated results before synchronization point is reached. This proposed method can effectively reduce the impact of one of the major performance-degrading factors in ED receivers, i. e., noise caused by heightened noise floor due to large bandwidth product. Our theoretic work on this im- proved synchronization performance and relevant simulations are conducted on IEEE 802.15.4a channel mod- els, and results show that the proposed design scheme can effectively decrease both the probability of false alarm and probability of missed detection.

Generalized Approach to Signal Processing in CollaborativeWireless Sensor Systems for Target Detection

Collaboration in wireless sensor systems must be fault-tolerant due to the harsh environmental conditions at which such systems can be deployed. This paper focuses on finding the signal processing algorithms for collaborative target detection based on the generalized approach to signal processing （GASP） in the presence of noise. The signal processing algorithms are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor systems. Two types of generalized signal processing algorithms, namely, value fusion and decision fusion constructed according to GASP in the presence of noise, are identified first. When comparing their performance and communication overhead, the decision fusion algorithm is found to become superior to the value fusion algorithm as the ratio of faulty sensors to fault free sensors increases. The use of GASP under designing the value and decision fusion algorithms in wireless sensor systems allows us to obtain the same performance, but at low values of signal energy, as well as under employment of the universally adopted signal processing algorithms widely used in practice.