Multi-target Case Research Articles

RIS-Assisted Cooperative Multicell ISAC Systems: A Multi-User and Multi-Target Case

RIS-Assisted Cooperative Multicell ISAC Systems: A Multi-User and Multi-Target Case

Greedy Integration Based Multi-Frame Detection Algorithm in Radar Systems

In this paper, we address the problem of detection and tracking of dim targets in radar systems through the use of multi-frame detection (MFD) techniques. We first study the energy expansion problem during multi-frame integration for classical MFD methods, which shows that the extended energy peak envelope poses a great challenge for target detection in nonhomogeneous backgrounds and multi-target cases. Next, a greedy integration based MFD algorithm is proposed, which separates the overall multi-frame joint maximization into two processes of confidence building and extended energy suppression. The proposed algorithm can eliminate the energy expansion intrinsically and achieve better detection performance with a lower implementation complexity. In addition, we extend the proposed algorithm to radar systems by deriving the accurate nonlinear conversion relationships between target states of Cartesian coordinates and echo measurements of polar coordinates. In radar scenarios, the proposed algorithm is capable to make detection adaptively after multi-frame integration through the use of traditional constant false alarm rate (CFAR) procedures. Finally, numerical results and tests with real radar data are presented to demonstrate the effectiveness of the proposed algorithm.

Consensus-based distributed two-target tracking over wireless sensor networks

This paper studies the target tracking problem over wireless sensor networks (WSNs). While most existing works on this problem focus on the single-target case and the few existing two-target tracking methods are based on linear observation models, we pay attention to the two-target tracking over WSNs, considering nonlinear targets’ dynamics and observation models. We divide all the sensors in the WSN into two groups corresponding to the two targets such that sensors in each group only observe one target but collect the information of the other one by communicating with the sensors in the other group. Then, the consensus-based distributed two-target tracking (CDTT) algorithms are proposed, applying the covariance intersection fusion rule to the information form of the extended Kalman filter. With this fusion rule, the consistency of the algorithms is guaranteed and the estimation accuracy is improved. Through analyzing the boundedness of the information matrices and the Lyapunov candidate defined on the estimation errors, we prove that the two-target tracking task can be completed by running the CDTT algorithms under certain conditions. Moreover, we extend the CDTT algorithms to the multi-target case, obtaining the consensus-based distributed multi-target tracking algorithms and showing their performance analysis. Simulation and experimental results are given to illustrate the performance of these tracking algorithms.

Fast k-Nearest Neighbor on a Navigation Mesh

We consider the k-Nearest Neighbour problem in a two-dimensional Euclidean plane with obstacles (OkNN). Existing and state of the art algorithms for OkNN are based on incremental visibility graphs and as such suffer from a well known disadvantage: costly and online visibility checking with quadratic worst-case running times. In this work we develop a new OkNN algorithm which avoids these disadvantages by representing the traversable space as a collection of convex polygons; i.e. a Navigation Mesh. We then adapt an recent and optimal navigation mesh algorithm, Polyanya, from the single-source single-target setting to the the multi-target case. We also give two new heuristics for OkNN. In a range of empirical comparisons we show that our approach can be orders of magnitude faster than competing methods that rely on visibility graphs.

Stereotactic radiosurgery commissioning and QA test cases-A TG-119 approach for Stereotactic radiosurgery.

To develop a standardized set of representative clinical treatment cases that pose a range of optimization problems for evaluating the plan quality and dosimetric accuracy within the commissioning process for linac-based stereotactic radiosurgery (SRS). Five test cases with increasing complexity were created to validate delivery accuracy in SRS commissioning similar to the approach used by AAPM TG-119 in developing a test suite for IMRT commissioning. Standardized structure sets, planning goals, and delivery requirements were specified for each case including a small sphere target, irregular target, irregular target placed off-axis, multi-target, and abutting organs-at-risk (OARs). Various VMAT field arrangements including a single arc, two coplanar arcs, full arc and vertex half arc, and four noncoplanar arcs were tested to generate clinically appropriate treatment plans. The small spherical target was 1.0cm in diameter. The irregular target was a clinical cavity (2.3×2.2×1.4cm³) and was shifted 4.5cm for the irregular target off-axis case. The multi-target case used the irregular target and four spherical targets representing metastases ranging 0.9 to 1.6cm in diameter, placed up to 7.5cm off-axis. The abutting OARs case included an acoustic neuroma and target placed near the optic nerve. All spherical targets received 24Gy and the cavity received 18Gy. The abutting OAR cases included a 3.74cc lesion adjacent to the brainstem receiving 13Gy and a 1.11cc lesion adjacent to the optic nerve receiving 12Gy. All plans used a single-isocenter placed at the target center or geometric center of multiple targets. Planning goals for all cases included constraints for the target and brain minus PTV, along with brainstem and optic nerve where applicable. Deliverability was assessed through ion chamber measurements, in addition to composite and per-field planar measurements on Gafchromic film and small-field diode array. A mean and SD for measured versus planned doses of 101.0%±2.9% was observed over the 14 ion chamber measurements. Mean and SD for gamma pass rates were 98.5%±2.2% and 97.1%±4.9% for film and diode array, respectively, for gamma criteria of 2% and 1mm. These cases could provide the preliminary groundwork for a novel benchmark for institutions to evaluate linac-based SRS commissioning and delivery accuracy prior to clinical implementation. The rapid widespread implementation of linac-based SRS, the complexity associated with dosimetry and delivery, and high-profile treatment deviations that have already resulted from its use, highlight the importance of such a benchmark test suite. Comprehensive dosimetric measurements from this standardized set of SRS optimization problems were used to fine-tune and understand the limitations of our SRS planning and delivery system and establish a set of baseline data for comparison with other delivery platforms.

Autonomous Aerial Dual-Target Following Among Obstacles

In contrast to recent developments in online motion planning to follow a single target with a drone among obstacles, a multi-target case with a single chaser drone has been hardly discussed in similar settings. Following more than one target is challenged by multiple visibility issues due to the inter-target occlusion and the limited field-of-view in addition to the possible occlusion and collision with obstacles. Also, reflecting multiple targets into planning objectives or constraints increases the computation load and numerical issues in the optimization compared to the single target case. To resolve the issues, we first develop a visibility score field for multiple targets incorporating the field-of-view limit and inter-occlusion between targets. Next, we develop a fast sweeping algorithm used to compute the field for the suitability of real-time applications. Last, we build an efficient hierarchical planning pipeline to output a chasing motion for multiple targets ensuring key objectives and constraints. For reliable chasing, we also present a prediction algorithm to forecast the movement of targets considering obstacles. The online performance of the proposed algorithm is extensively validated in challenging scenarios, including a large-scale simulation, and multiple real-world experiments in indoor and outdoor scenes. The full code implementation of the proposed method is released here: https://github.com/icsl-Jeon/dual_chaser .

Sequential Estimation of Frequency and Direction-of-Arrival Based on the Relaxed Coprime Array for Multiple Targets

Recently, extensive researches focus on the joint estimation of carrier frequency and direction-of-arrival, whereas the heavy computation burden and affordable hardware cost are always required therein. To alleviate the problem, we propose a relaxed coprime array based two-stage estimator, which can sequentially detect the frequencies and direction-of-arrival for multiple targets. Guided by the closed-form robust algorithm, this relaxation yields a higher array sparsity compared with existing sparse arrays. Specifically, the first stage aims to achieve the classification of the frequency and angle remainders arising from temporal-spatial undersampling, which is realized by combining spectrum correction with pattern clustering. By incorporating the closed-form robust Chinese Remainder Theorem into the remainder classification result, we obtain all the frequencies and direction-of-arrival in the second stage. Both performance analysis and numerical results were conducted to verify the effectiveness of the proposed estimator in the multi-target case.

The Pairwise-Markov Bernoulli Filter

The Bernoulli filter is a general, Bayes-optimal solution for tracking a single disappearing and reappearing target, using a sensor whose observations are corrupted by missed detections and a general, known clutter process. Like virtually all target-tracking algorithms it presumes restrictive independence assumptions, namely a hidden Markov model (HMM) structure on the sensor and target. That is, the current state of the target depends only on its previous state, and the measurement collected from it depends only on its current state. Pieczynski's pairwise Markov model (PMM) relaxes these restrictions. In it, the current target state can additionally depend on the previous measurement; and the current measurement can additionally depend on the previous measurement and previous target state. In this paper we show how to correctly generalize the PMM to the multitarget (MPMM) case; and use the MPMM to derive a “PMM Bernoulli filter” that obeys PMM rather than restrictive HMM sensor/target statistics.

Attractive passive direct positioning algorithm for localisation of multiple transmitters based on eigenvalue maximizing

In terms of the passive position determination problem, the most commonly used methods are based on two-step processing. While here, the authors propose a technique that estimates the locations of transmitters by processing the raw signals from all receivers at the central processor, which belongs to the direct position determination (DPD) concept. There are already efforts made on single target localisation through eigenvalue maximising based on the DPD technique. While the multi-target case encountered more commonly in realistic scenarios. By additionally combined with the image expansion algorithm, the sources can be extracted effectively and their positions are determined simultaneously. Simulation results illustrate that the localisation accuracy for each transmitter is equivalent to the two-step based approach at high signal-to-noise ratio (SNR). While for low SNR, the superiority and accuracy of the proposed method are also manifested.

A Scheme for Multitarget Lateral Velocity Measurement With High-Frequency Monostatic Radar

This paper proposes a method for extracting the lateral velocity in multitarget cases to improve the ship tracking capability of high-frequency surface wave radar (HFSWR). The method exploits the phase interferometry between two antenna arrays that is done in the time domain after joint frequency–azimuth filtering. First, a frequency filter based on generalized S transform with a variable factor is applied to eliminate the background noise. The variable factor is linked to the target's radial velocity and can control the time and frequency resolutions. We then use two identical subarrays as two receiving channels to implement the azimuth filtering. Based on adaptive minimum-variance distortionless response beamforming, the extraneous signals can be suppressed. Subsequently, the varying slope of the phase difference of the target of interest signal from two channels can be extracted to compute the lateral velocity in a low signal-to-noise ratio scenario. The interference of noise and extraneous target signals is analyzed using simulations, and the effectiveness of the frequency–azimuth filtering method is validated with both simulations and experimental data. In addition, the high spatial resolution ship tracking results over an hour match well with automatic identification system data, demonstrating the feasibility of tracking targets with HF monostatic radar.

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor.

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified.

Comparative Study of Combined CFAR Algorithms for Non-Homogenous Environment

The combination of different CFARs algorithms has been done to overcome the limitations of individual ones with different return signals in the non-homogenous environment. A comparative study of two kinds of algorithms; the combination between CFAR in the same family and diverse families. TM, AND, OR, CASH, ACGCA-CFAR algorithms have been tested with four kinds of return signals, single, multi, close targets and clutter edge. Also, the probability of detection has been evaluated for these algorithms. This study appears that the CASH, OR and TM have an overperform than the other in the multi-target case, while the ACGCA, VI, and TM are advance the other in the adjacent target state, in this context, the OR, VI, and ACGCA are best in clutter edge case. In this study, the Matlab 2015b is used to evaluate the performance of different types of CFAR algorithms.

A New Iterative Approach in SINR Improvement of MIMO Radars by Using Combination of Orthogonal Waveforms

In this paper we consider joint waveform and filter design in multi-input multi-output (MIMO) radars in the presence of signal dependent interference to improve signal-to-interference-plus-noise ratio (SINR) of received signals. We have proposed two new iterative methods for this in which instead of direct design of waveforms, the coefficients of orthogonal waveform combinations are designed. In the first method, coefficients of combinations are calculated by solving a convex optimization problem. By extending the first method, we have proposed a method for multi-target case in presence of signal dependent interference. However, the computational complexity of the first method is high and therefore we have proposed the second method, which is more suitable for real time applications. In the second method, in each step, waveform combination coefficients and received filter coefficients are designed in closed form. Simulation results show that the proposed methods can achieve higher SINR in comparison to other methods which are used in MIMO and phased array radars.

DOA estimation of multiple sources in sparse space with an extended array technique

An algorithm to improve direction of arrival (DOA) estimation accuracy with an extended sensor array in the presence of multiple coherent signal sources is proposed. The algorithm uses virtual element theory to extend the sensor array, estimates virtual element information via linear prediction and expands the array aperture in practical sense; the sparsity of the target orientation in angle space is exploited to establish an over-complete dictionary and a reception model for the array signal in sparse space; the received array data is preprocessed using singular value decomposition (SVD) method and target DOA estimation is realized by calculating the best atoms. The algorithm improves DOA estimation accuracy by extended array and uses SVD to control computational complexity effectively, which ensures the accuracy and efficiency. Computer simulation shows that the proposed algorithm is able to accurately estimate the DOA for both single-target and closely spaced multi-target cases in low signal-to-noise ratio environments, and also has excellent DOA estimation performance in the presence of multiple coherent signal sources.

Investigation of two linear accelerator head designs for treating brain metastases with hypofractionated volumetric-modulated arc radiotherapy.

To investigate brain radiation dose in complex cases arising from two stereotactic linear accelerator designs and to present a method for comparing brain dose to published data. Two head designs were considered: Beam Modulator (BM) and Agility (AG). 12 patients treated on BM were replanned with AG. Planning objectives were: minimize brain dose and satisfy target coverage and organs at risk dose constraints. Each of the 36 targets was analyzed for conformality index (CI Paddick), gradient index (GI) and homogeneity index (HI). Total volume of tissue receiving 80% (V80) of the prescription dose down to 25% (V25) was evaluated. Similarly the volume of brain minus planning target volume receiving 80% (BMP80) down to 25% (BMP25) was evaluated. The mean brain dose and BMP dose were also evaluated. System differences were statistically evaluated using Wilcoxon signed-rank test. Power-law models for total volume (V) and brain minus planning target volumes (BMP) were generated based on BM data. The median CI Paddick was 0.74 and 0.76 for BM and AG, respectively (p = 0.04). The median GI was 5.5 and 6.1 (p < 0.01) and the median HI was 1.17 and 1.16 for BM and AG, respectively (p < 0.01). Neither V or BMP receiving doses of 80% down to 40% exhibited statistically significant difference between the two systems, whereas the volume of brain minus PTV receiving 25% (BMP25) was weakly different (p = 0.02). AG exhibited a lower mean BMP dose (4.1 Gy) than BM (4.6 Gy) (p < 0.01). Power-law models for V/BMP showed excellent (R(2) > 0.80) agreement for the dose levels studied and comparable results with published data. Treatment plans of equivalent quality were attained with AG compared with BM. The AG system involves a novel collimation design. The present article demonstrates equivalent or improved brain dose for complex, multitarget cases using AG vs an older stereotactic system.

Scalable Semi-Automatic Annotation for Multi-Camera Person Tracking.

This paper proposes a generic methodology for the semi-automatic generation of reliable position annotations for evaluating multi-camera people-trackers on large video data sets. Most of the annotation data are automatically computed, by estimating a consensus tracking result from multiple existing trackers and people detectors and classifying it as either reliable or not. A small subset of the data, composed of tracks with insufficient reliability, is verified by a human using a simple binary decision task, a process faster than marking the correct person position. The proposed framework is generic and can handle additional trackers. We present results on a data set of $sim 6$ h captured by 4 cameras, featuring a person in a holiday flat, performing activities such as walking, cooking, eating, cleaning, and watching TV. When aiming for a tracking accuracy of 60 cm, 80% of all video frames are automatically annotated. The annotations for the remaining 20% of the frames were added after human verification of an automatically selected subset of data. This involved $sim 2.4$ h of manual labor. According to a subsequent comprehensive visual inspection to judge the annotation procedure, we found 99% of the automatically annotated frames to be correct. We provide guidelines on how to apply the proposed methodology to new data sets. We also provide an exploratory study for the multi-target case, applied on the existing and new benchmark video sequences.

MIMO Radar Adaptive Waveform Design for Extended Target Recognition

The problems of multiple-input multiple-output (MIMO) radar adaptive waveform design in additive white Gaussian noise channels and multitarget recognition based on sequential likelihood ratio test are jointly addressed in this paper. Two information-theoretic waveform design strategies, namely, the optimal waveform for maximizing the mutual information (MI) between the extended target impulse response and the target echoes and the optimal waveform for maximizing the Kullback-Leibler (KL) divergence (or relative entropy), are applied in the multitarget recognition application. For multitarget case, two adaptive waveform design methods for all possible targets based on the current knowledge of each hypothesis are proposed. Method 1 is the probability weighted waveform method. Method 2 is the probability weighted target signature method. The optimal waveform is transmitted and adaptively changed such that a decision is made based on the likelihood ratio after several illuminations. Numerical results demonstrate that the best waveform is the KL divergence-based optimal waveform using Method 1 as it has the lowest average illumination number and the highest correct decision rate for target recognition. By optimally designing and adaptively changing the transmitted waveform, the average number of illuminations required for multitarget recognition can be much reduced.

Assessment for the Utility of Treatment Plan QA System according to Dosimetric Leaf Gap in Multileaf Collimator

For evaluating the treatment planning accurately, the quality assurance for treatment planning is recommended when patients were treated with IMRT which is complex and delicate. To realize this purpose, treatment plan quality assurance software can be used to verify the delivered dose accurately before and after of treatment. The purpose of this study is to evaluate the accuracy of treatment plan quality assurance software for each IMRT plan according to MLC DLG (dosimetric leaf gap). Novalis Tx with a built-in HD120 MLC was used in this study to acquire the MLC dynalog file be imported in MobiusFx. To establish IMRT plan, Eclipse RTP system was used and target and organ structures (multi-target, mock prostate, mock head/neck, C-shape case) were contoured in I'm RT phantom. To verify the difference of dose distribution according to DLG, MLC dynalog files were imported to MobiusFx software and changed the DLG (0.5, 0.7, 1.0, 1.3, 1.6 mm) values in MobiusFx. For evaluation dose, dose distribution was evaluated by using 3D gamma index for the gamma criteria 3% and distance to agreement 3 mm, and the point dose was acquired by using the CC13 ionization chamber in isocenter of I'mRT phantom. In the result for point dose, the mock head/neck and multi-target had difference about 4% and 3% in DLG 0.5 and 0.7 mm respectively, and the other DLGs had difference less than 3%. The gamma index passing-rate of mock head/neck were below 81% for PTV and cord, and multi-target were below 30% for center and superior target in DLGs 0.5, 0.7 mm, however, inferior target of multi-target case and parotid of mock head/neck case had 100.0% passing rate in all DLGs. The point dose of mock prostate showed difference below 3.0% in all DLGs, however, the passing rate of PTV were below 95% in 0.5, 0.7 mm DLGs, and the other DLGs were above 98%. The rectum and bladder had 100.0% passing rate in all DLGs. As the difference of point dose in C-shape were 3∼9% except for 1.3 mm DLG, the passing rate of PTV in 1.0 1.3 mm were 96.7, 93.0% respectively. However, passing rate of the other DLGs were below 86% and core was 100.0% passing rate in all DLGs. In this study, we verified that the accuracy of treatment planning QA system can be affected by DLG values. For precise quality assurance for treatment technique using the MLC motion like IMRT and VMAT, we should use appropriate DLG value in linear accelerator and RTP system.

Understanding the Role of Political Relations in Consumer Decision Making: A Grounded Theory Approach

Previous animosity studies have been conducted in single-target contexts where the effects of hostility towards one product’s country of origin were examined. This current study is an attempt to investigate the animosity construct in the multi-target boycott case of the Middle-East conflict where more than one party (countries and companies) are involved in the political conflict, as reports show that consumers have inconsistent reactions to these involved parties. One-on-one in-depth interviews, supported by documentation, were conducted with Arab consumers who are presumably involved in the conflict. It has been found that animosity is multi-level which belongs to the political relations (there after POLR) continuum and performs as a product attribute. POLRs’ effects on the consumer are subject to parties’ involvement level in the conflict and consumer prioritized needs. Research findings imply that “political positioning” can be applied by brands with “good quality” POLR, while others need to highlight other product attributes.

The Orthonormalized Volume Magnetic Source Model for Discrimination of Unexploded Ordnance

We introduce a fast and accurate numerical technique for the solution of electromagnetic induction sensing problems called the orthonormalized volume magnetic source model. The model assumes that the secondary magnetic field measured by a sensor originates from a set of magnetic dipole sources distributed over a volume that coincides with the interrogated area. The Green functions associated with the responding sources are turned into an orthonormal basis using a generalization of the Gram-Schmidt method, enabling one to determine the sources' strengths directly from measured data without having to invert large and potentially ill-conditioned matrices. The method treats multitarget cases naturally and robustly. Several examples are presented to illustrate the applicability of the method in the discrimination of unexploded ordnance (UXO). In particular, we analyze data taken by the Time-Domain Electromagnetic Multisensor Towed Array Detection System sensor array at a test stand and during a blind test administered at a UXO live site. The method is highly successful in distinguishing UXO from among other UXO and from accompanying clutter.