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Adopting low-resolution analog-to-digital converters (ADCs) for receive antennas of a multiple-input multiple-output (MIMO) system can remarkably reduce the hardware cost, circuit power consumption as well as amount of data to be transferred from RF components and the baseband-processing unit. However, an obvious performance loss is also expected. Towards this end, in this work we introduce a new architecture which contains both high- and low-resolution ADCs (named as high-mix-low-resolution ADCs) for collocated MIMO radar, and the associated problem of waveform design is discussed in detail. Specifically, the problem jointly optimizes the waveform, ADC switch vector and receive filter, so as to maximize the signal-to-interference-plus-quantization-error-and-noise ratio (SIQENR). To tackle the resultant nonconvex problem, an alternating optimization method (AOM) is devised. To be more specific, the ADC switch vector and waveform matrix are optimized with the block successive upper-bound minimization (BSUM) framework based on the Dinkelback method. Furthermore, a continuous and concave function is introduced to approximate the $ l_0$ norm to achieve a binary solution of the ADC switch vector. It is shown that the optimal solutions to the ADCs switch vector and waveform matrix can be efficiently attained by using the alternating direction method of multipliers (ADMM) approach and Karush-Kuhn-Tucher (KKT) conditions, respectively. Numerical simulations are provided to demonstrate the effectiveness of the proposed schemes.

Low-temperature heat source has been exploited for decades to generate electricity. Organic Rankine cycle (ORC) system has a high energy conversion efficiency due to the good performance of organic fluids under the low-temperature heat source. In this study, a double-pressure organic Rankine cycle system driven by low-temperature heat source is used to generate electricity. The double-pressure ORC system achieves the cascaded utilization of energy, which can improve the efficiency of energy conversion. Geothermal heat source is employed as a typical low-temperature heat source. Mathematical model is established based on thermodynamic and economic laws, and the overall system performance has been evaluated. Parametric analysis is conducted to examine the effects of some key thermodynamic parameters, namely turbine high-level inlet pressure, turbine low-level inlet pressure, turbine high-level inlet temperature, on the system's performance. Multi-objective Parametric optimization based on turbine 1-D design is conducted by means of genetic algorithm (GA) to find the best operation conditions for both economic and thermodynamics. At the same time, the performances of three organic working fluids are examined. Results indicate that the double-pressure ORC system has a better performance than single-pressure ORC system, and R245fa has a better performance among three organic fluids. It is also found that the exergy efficiency has a peak value with the change of turbine high-level inlet pressure and turbine low-level inlet pressure. In addition, increasing turbine high-level inlet temperature brings a positive effect on the system performance. Exergy analysis is also conducted and the result indicated that the main exergy loss occurs in high-pressure evaporator. After system optimization, the double-pressure organic Rankine cycle has a better performance in utilizing geothermal energy than single-pressure system.

This paper considers the problem of co-existence of collocated multiple-input multiple-output (MIMO) radar and downlink multiple-input single-output (MISO) communication systems, which share the same frequency band. As the interference caused by the communication systems would degrade the accuracy of radar target localization, we formulate the co-design of radar waveform and communication transmit weights by minimizing the Cramer-Rao Bound (CRB) of direction-of-arrival (DOA) estimation, subject to a set of constraints accounting for the worst-case signal-to-noise-plus-interference ratio (SINR), similarity and energy. However, the objective is nonconvex and all variables are coupled together in the SINR constraints, the formulated problem is thus NP-hard. Towards that end, a decentralized block successive upper-bound minimization (D-BSUM) method based on the decomposition theory is developed. More specifically, at each iteration of this algorithm, the radar waveform is obtained with the aid of the alternating direction method of multipliers (ADMM) algorithm, and communication weights are obtained by exploiting the semidefinite programs (SDP). It is also proved that the proposed SDP-based method gives a rank-one solution. Numerical simulations are conducted to evaluate the effectiveness of the proposed algorithm.

It is known that deploying low-resolution (e.g., one-bit) analog-to-digital converters (ADCs) at the receive antennas can reduce the hardware cost and circuit power consumption, especially for large-scale systems. In this context, we investigate the performance of target detection for collocated multiple-input multiple-output (MIMO) radar with one-bit ADCs. Considering a scenario where the transmit-receive channel matrix suffers from uncertainty with a known distribution, a one-bit likelihood ratio test (LRT) detector is derived. Moreover, the asymptotic performance of this detector is analyzed. Numerical simulations are performed to demonstrate our theoretical analysis and evaluate the performance of the one-bit LRT detecor.

Deploying low-resolution (e.g. one-bit) digital-to-analog converters (DACs) is of great importance in the multiple-input multiple-output (MIMO) system equipped with a large-scale antenna array since such a hardware architecture brings low-cost and circuit power saving for each antenna. In this paper, the problem of transmit signal design in a large-scale MIMO system with 1-bit DACs is investigated. To ensure directional transmission, we propose to design the transmit signal by minimizing the weighted mean-squared error (MSE) between the formed beampattern and a given one. The resulting design problem, which involves a nonconvex fourth-order objective and a set of nonconvex discrete constraints, is NP-hard, and therefore, an alternating minimization (AM) method is devised. In order to obtain a high-quality 1-bit solution, we propose a continuous and differentiable function to approximate the 1-bit signal, such that the problem with discrete 1-bit constraint is recast to an unconstrained optimization problem with a penalty term, which can be effectively solved via the limited-memory Broyden, Fletcher, Goldfarb, and Shanno (L-BFGS) approach. Moreover, it is found that a closed-form solution can be obtained when equal weights are applied. In addition, low-complexity schemes are developed based on the fast Fourier transform (FFT). The numerical simulations are conducted to demonstrate the effectiveness and superiority of the proposed method.

This paper design waveform for high frequency radar to optimize its performances in co-channel interference/colored noise environment. Considering that radar applies the optimal filter for range processing, a novel objective function accounting for both Signal to Interference plus Noise Ratio (SINR) and Integrated Sidelobes Level (ISL) is introduced and the constant modulus constraint on the probing waveform is forced. To resolve the resulting non-convex quartic optimization problem, an efficient iterative algorithm based on Majorization-Minimization (MM) and Pattern Search (PS) is proposed. In each iteration, the proposed algorithm produces a multi-dimension quadratic majorized problem and then splits it into multiple one-dimension problems with closed-form solutions. Simulation results show that the SINR and ISL performances of designed waveform can be flexibly adjusted. Besides, the convergence speed and stability of the proposed algorithm are more satisfactory than the other methods.

This paper investigates the design of constant modulus waveforms with low auto- and cross-correlation sidelobes for multiple-input multiple-output (MIMO) radar. The resulting weighted integrated sidelobe level (WISL) minimization problem involves a fourth-order objective function and nonconvex constant modulus constraint and, hence, is NP-hard. Unlike existing methods which indirectly solve an “almost equivalent” problem to the original one, we equivalently reformulate the nonconvex WISL minimization problem appropriately and propose a new method to directly deal with the problem. Specifically, in the proposed algorithm, the fourth-order problem is first converted into a bi-quadratic problem via introducing an auxiliary primal variable, and then a primal-dual framework, named as “nonlinear alternating direction method of multipliers (nonlinear-ADMM)”, is derived to handle the modified problem. More importantly, both the convergence and termination conditions of this algorithm are discussed. Numerical simulation are carried out to assess the performance of the proposed algorithm in terms of the WISL metric, auto- and cross- correlation properties and computational complexity.

Designing the radar waveform, which ensures spectral compatibility with the communication systems, is known to be challenging. In addition to having the desirable transmitter efficiency, it is also anticipated to share the good pulse compression property of the reference waveform. In this paper, we investigate the problem of waveform design for multiple-input multiple-output radar with good transmit beampattern under certain practical constraints (e.g., peak to average power ratio and similarity constraints) in coexistence with communication systems. The waveform is designed by minimizing a weighted summation of the beampattern integrated sidelobe-to-mainlobe ratio and waveform energy over the space-frequency bands. Since the resulting problem is NP-hard, two approximated primal-dual algorithms based on the alternating direction method of multipliers algorithm are proposed. Concretely, the proposed algorithms update the primal variable by minimizing the linearized and quadratic approximations of the augmented Lagrangian function of the original problem, respectively. The closed-form solution of each primal variable is provided. Moreover, both the convergence and computational complexities of these two algorithms are discussed. Numerical simulations are provided to demonstrate the effectiveness of the proposed approaches.

In this paper, the problem of transmit beampattern synthesis (i.e., transmit beamforming) in multiple input multiple output (MIMO) radar which deploys one-bit digital-to-analog converts (DACs) is investigated. We aim to design appropriate transmit signal sequences, which are quantized by one-bit DACs, such that the amount of transmit energy can be focused into mainlobe region as much as possible, meanwhile, the leakage power of sidelobe region is minimized. It is shown that these requirements can be simultaneously fulfilled by minimizing the integrated sidelobe to mainlobe ratio (ISMR) of transmit beampattern with discrete binary constraints. According to this concept, we utilize the alternating direction multiplier method (ADMM) framework to solve the resulting nonconvex problem. Simulation results will demonstrate the effectiveness and improved performance of the proposed method.

This paper focuses on the problem of the optimization of nodes positions for sparse large aperture radar (SLAR) system. To overcome the deficiency of low target search efficiency in traditional SLAR system, a search scheme based on grating lobe controlling, in which the SLAR system searches multiple directions simultaneously by utilizing a transmit beampattern with multiple grating lobes, is provided. More specifically, the relationship between the nodes positions and grating lobes is mathematically discussed. On this basis, under the practical node position constraint, a design method of nodes positions for synthesizing a beampattern with desired grating lobes and low sidelobes is presented. Some representative simulations are provided to validate the effectiveness of the proposed scheme.

This paper proposes an optimization scheme for collocated multiple-input-multiple-output (MIMO) radar with a partial low-resolution ADCs architecture. With a criterion of the signal-to-interference plus quantization noise ratio (SIQNR) maximization, we formulate our problem by jointly optimizing the waveform, ADC switch vector and receive filter. Since the resultant problem is nonconvex, an alternating optimization framework (AOF) is proposed. Specifically, the block successive upper-bound minimization (BSUM) framework based on the Dinkelback method is devised to optimize the ADC switch vector and waveform matrix. Moreover, we propose a continuous and concave function to approximate the $l_{0}$ norm to obtain a high-quality sparse solution to the ADC switch vector. Numerical simulations are provided to demonstrate the effectiveness of the proposed schemes.

This paper addresses the long-time coherent integration detection problem for a weak maneuvering target, involving linear range migration (LRM), range curvature (RC), and Doppler frequency migration (DFM). To solve the above problems, an efficient coherent integration method based on frequency phase compensation function process (FPCFP) is proposed. By jointly searching the unknown motion parameters in velocity and acceleration domains, the FPCFP algorithm not only can eliminate LRM, RC, and DFM simultaneously, but also can realize the coherent integration. Compared with the existing algorithms, the proposed method achieves a better detection probability in a low signal-to-noise ratio (SNR) environment and ensures high computational efficiency. Several experiments are performed to verify the effectiveness of the presented approach.

This paper investigates a hybrid beamforming design for multi-user dual-function radar-communication (DFRC) system. The hybrid transmit/receive beamformers are designed by maximizing the sum-rate under constraints of power as well as similarity between the designed beamformer and the reference one that has good beampattern property. To solve the nonconvex optimization problem, we devise a two-stage method. To be more specific, in the first stage, we obtain the fully digital beamformer based on the weighted mean-square error minimization (WMMSE) method, in the second stage, we iteratively optimize the digital and analog beamformers to approximate the achieved fully digital beamformer. Numerical simulations are provided to demonstrate the effectiveness of the proposed schemes.

Considering the high sidelobe of the MVDR beamformer, a sparse constraint on beam pattern has been suggested to suppress the sidelobe of adaptive beamformer. Based on the sparse constraint, a modified Capon spectrum is proposed to form a new beamformer to compensate for the lack of robustness of the MVDR beamformer. In proposed method, the constructed penalty matrix gives the minimum penalty on the mainlobe region to keep its shape in existing steering vector error and meanwhile the positions of interferences distinguished from the sidelobe region by the modified Capon spectrum are imposed a larger penalty to obtain a performance of interference suppression as perfect as the MVDR beamformer's. What's more, the sidelobe level in our method is moderately controllable. Finally, an algorithm of the alternating direction method of multipliers (ADMM) is suggested to solve the problem efficiently. Numerical examples show the advantages of the proposed method in adaptive beamforming.

This paper investigates the problem of hybrid transceiver design for dual-functional radar-communication (DFRC) system. Specifically, we introduce an information embedding scheme for the DFRC system with a subarray structure. The hybrid transmit/receive beamformers are designed by maximizing sum-rate under constraints of power and similarity between the designed bemaformer and the reference one with good beampattern property. Since the formulated problem is difficult to tackle, we propose an alternating optimization method based on the alternating direction method of multipliers (ADMM) framework to obtain the hybrid beamformer. Numerical simulations are provided to demonstrate the effectiveness of the proposed schemes.

In this paper, the problem of transmit beampattern design in multiple-input multiple-output (MIMO) radar with one-bit digital-to-analog converts (DACs) is investigated. The one-bit waveform sequence can be properly designed by minimizing the integrated sidelobe to mainlobe ratio (ISMR) of the transmit beampattern. However, due to the minimum ISMR criterion and discrete constraint, the formulated optimization problem for such a design is nonconvex and thus difficult to tackle directly. To this end, we employ the semidefinite relaxation (SDR) technique to modify the original problem to its convex counterpart. More importantly, the dimension of resulting large-scale semidefinite programming (SDP) problem is greatly reduced via exploiting the special block-spare structure. Simulation results will demonstrate the effectiveness and improved performance of our method.

This paper investigates the problem of angle measuring of the target in the presence of jammings with planar arrays. The relationship between the quiescent monopulse ratios and azimuth/elevation is first studied. On this basis, the distortion of the surface of the conventional minimum variance distortionless response monopulse ratio is analyzed. In order to avoid such distortion and approximate the adaptive monopulse ratio surface to the quiescent one, an adaptive monopulse approach with joint linear constraints on both the azimuth and elevation is proposed. Simulation results demonstrate that the proposed approach is capable of attaining a high angle measuring accuracy in the presence of mainlobe jammer.

The paper investigates the joint design of transmit waveform and receive filter for multiple-input multiple-output radar in the presence of signal-dependent interference, subject to a peak-to-average-power ratio constraint as well as a waveform similarity constraint. Owing to this kind of signal dependence and constraints, the formulated optimization problem of the output signal-to-interference-plus-noise ratio (SINR) maximization is NP-hard. To this end, an auxiliary variable is first introduced to modify the original problem, and then a primal-dual algorithm based on the block successive upper-bound minimization method of multipliers (BSUM-M) is developed to deal with the resulting problem. Moreover, an active set method is exploited to solve the quadratic programming problem involved in each update procedure of the proposed BSUM-M algorithm. Finally, numerical simulations are performed to demonstrate the superiority of the proposed algorithm over state-of-the-art methods in terms of the output SINR, beampattern, computational complexity, pulse compression, and ambiguity properties.

Exploiting renewable energy could greatly alleviate current severe energy situation. Transcritical CO 2 (tCO 2 ) cycle system as a type of competitive and promising energy converter could utilize low temperature geothermal energy effectively. In this paper, the methodology for the off-design operation of tCO 2 system has been proposed and the quantitative performance analysis is carried out for the utilization of geothermal energy. With the aim at obtaining better thermodynamic and economic performance, the optimal power cycle parameters can be determined by the non-dominated sorting genetic algorithm-II (NSGA-II) in the design stage. The models of exergoeconomic analysis and main system components including turbine, pump and heat exchangers are established. The sliding pressure control strategy is applied to respond to the varieties of heat source and heat sink conditions in the off-design stage. Results show that there exists an optimal value of geothermal resource mass flow rate to maximum the thermal efficiency. The pump rotational speed increases linearly with the increasing geothermal resource temperature and geothermal resource mass flow rate while the pump rotational speed is gradually sensitive to the increase of heat sink temperature. The guideline listed in the table for pump could provide effective reference for practical operation.

In this Letter, the problem of waveform design for MIMO radar with good transmit beampattern performance is investigated. The binary transmit waveforms are designed via minimising the beampattern integrated sidelobe to mainlobe ratio. Since the resulting binary combination optimisation problem is NP-hard, a generalised likelihood ascent search algorithm is proposed to deal with it. Besides, the effectiveness of the proposed algorithm is demonstrated via simulation results.

This paper considers the problem of transmit beampattern synthesis (i.e., transmit beamforming) in multiple-input multiple-output (MIMO) radar which deploys one-bit digital-to-analog converts (DACs). By appropriately designing the transmitted signal waveforms quantized by one-bit DACs, the majority of radiated energy can be focused into the mainlobe(s) region to enhance the intensity of backscattered signals from targets. Meanwhile, the amount of energy inevitably leaked into the sidelobe region is minimized to suppress the interferences. More specifically, the essence of the proposed design can be regarded as optimizing the one-bit signal waveforms such that the synthesized transmit beampattern has a minimum integrated-sidelobe-to-mainlobe ratio (ISMR). In order to tackle the nonconvex discrete constraint in the resulting optimization problem, we propose to introduce auxiliary variables to reformulate the discrete constraint into continuous constraints. On this basis, the alternating direction multiplier method (ADMM) framework is applied to deal with the reformulated problem. The proposed method can approximately solve the sub-problems with closed-form solutions in each iteration, and hence, it is computationally efficient. Simulation results indicate that the proposed method is able to provide promising performance.

A multiple-input multiple-output radar has great flexibility to design the transmit beampattern via selecting the probing waveform. The idea of current transmit beampattern design is to approximate the disired transimit beampattern and minimize the cross-correlation sidelobes. In this paper, under the constant modulus constraint, two algorithms are proposed to design the probing waveform directly. In the first algorithm, the optimization criterion is minimizing the squared-error between the designed beampattern and the given beampattern. Since the objective function is a nonconvex fourth-order polynomial and the constant modulus constraint can be regarded as many nonconvex quadratic equality constraints, an efficient alternating direction method of multipliers (ADMM) algorithm, whose convergence speed is very fast, is proposed to solve it. In the second algorithm, the criterion is minimizing the absolute-error between the designed beampattern and the given beampattern. This nonconvex problem can be formulated as $l_1$ -norm problem, which can be solved through a double-ADMM algorithm. Finally, we assess the performance of the two proposed algorithms via numerical results.

Geothermal energy, as a typical low-temperature heat source, has been exploited for decades to generate electricity. Organic Rankine cycle (ORC) system has a high energy conversion efficiency due to the good performance of organic fluids under the geothermal water temperature. In this study, a double-pressure organic Rankine cycle system driven by geothermal heat source is used to generate electricity. The double-pressure ORC system achieves the cascaded utilization of energy, which can improve the efficiency of energy conversion. Mathematical model is established based on thermodynamic laws, and the overall system performance has been evaluated. A parametric analysis is conducted to examine the effects of some key thermodynamic parameters, namely turbine high-level inlet pressure, turbine low-level inlet pressure, turbine high-level inlet temperature, on the system performance. Parametric optimization is conducted by means of genetic algorithm (GA) to find the maximum system performance. At the same time, the performances of three organic working fluids are examined. Results indicate that R245fa has a better performance among the three organic fluids. The exergy efficiency of overall system exceeds 5.8% under the supply water of 120℃, and it produce more than 800kW electricity with the geothermal water at the mass flow rate of 250t/h. It is also found that the exergy efficiency has peak value under the effect of turbine high-level inlet pressure and turbine low-level inlet pressure. In addition, increasing turbine high-level inlet temperature brings a positive effect to the system performance. Exergy analysis is also conducted and the result shows that the main exergy loss occurs in high-pressure evaporator. By system optimization, the double-pressure organic Rankine cycle has a better performance in utilizing geothermal energy than single-pressure system.

This paper focuses on the problem of coexistence between a colocated multiple-in multiple-out (MIMO) radar and down-link communication systems. We propose an iterative algorithm to minimize the Cramer-Rao Bound (CRB) on the direction of arrival (DOA) of a target, accounting for the energy and similarity constraints. More Specifically, at each iteration of this algorithm, the radar waveform is obtained with the aid of the alternating direction method of multipliers (ADMM) algorithm, and then the communication weights are obtained by exploiting the block successive upper-bound minimization method (BSUM). Finally, numerical results are presented to evaluate the effectiveness of the proposed algorithm.

In this paper, we investigate the problem of transmit beam-pattern design for MIMO radar with one-bit DACs. Based on the Fast Fourier Transform (FFT), we propose an alternating minimization (AM) method to minimize the weighted squared-error (WSE) between the designed beampattern and a given one. In particular, we propose an approximation approach to achieve a high-quality solution with one-bit constraint. Finally, numerical simulations demonstrate that the effectiveness of the proposed method.

In this paper, we focus on the waveform optimization problem of transmit beampattern design for a multiple-input multiple-output (MIMO) radar with low matched filtering range sidelobes (MFRS). The waveform is designed by minimizing a weighted summation of the transmit beampattern matching errors and the MFRS level under constant modulus constraint. Since the resulting problem is NP-hard, some auxiliary variables are introduced to recast it as a bi-convex quadratic problem, and then the alternating direction method of multipliers (ADMM) algorithm is applied to efficiently solve it. Finally, simulation results are presented to validate our approach.

This paper deals with grating-lobe clutter suppression problem by designing the transmit beamforming (TB) in the uniform subarray (US) configuration. In order to suppress the grating-lobe clutter of the main-lobe area in the conventional space-time adaptive processing (STAP), we propose an appropriate TB in an active array. Firstly, we utilize the information of grating-lobe locations and the respective clutter power to construct a transmit covariance matrix (TCM). Then, the TB can be designed resorting to the minimum variance distortionless response (MVDR) algorithm with the reconstructed TCM. Numerical results illustrate that the proposed method can mitigate the grating-lobe clutter effectively with a higher output signal-to-clutter-plus-noise ratio (SCNR) than traditional STAP.

This paper investigates the design of constant modulus waveforms with low auto- and cross-correlation sidelobes for multiple-input multiple-output (MIMO) radar. Unlike existing methods which indirectly solve an “almost equivalent” problem to the original one, we propose a new method to directly deal with the problem. Specifically, in the proposed algorithm, the fourth-order problem is first converted into a bi-quadratic problem via introducing an auxiliary primal variable, and then a primal-dual framework, named as “nonlinear alternating direction method of multipliers (nonlinear-ADMM)”, is derived to handle the modified problem. Moreover, the solution of each primitive variable can be computed efficiently. Numerical simulations are carried out to assess the performance of the proposed algorithm in terms of the WISL metric, auto- and cross- correlation properties and computational complexity.

In order to solve the disadvantage of conventional structuring element (CSE) where amplitude does not change in accordance with the analyzed signal, the quantum theory is combined and a nonlinear quantum-inspired weighting structuring element (NQWSE) is proposed. The NQWSE which is utilized to extract the bearing impulse response signal can adjust its amplitude according to the mechanical signal. Firstly, after constructing the multiple quantum bits system for signals, the mapping method which is employed to map the quantum space to the real space is presented and the parameters of the mapping method are set. The nonlinear amplitude probability is calculated based on the stochastic characteristics of the bearing signals, while the dynamic amplitude is calculated based on the local feature of the bearing signals in a subwindow. Then the mathematical formula of NQWSE is derived by incorporating the mathematical expectation into the quantum theory and the mapping method. Finally, the NQWSE is applied to extract the fault information of a failure bearing. The results reveal that NQWSE can extract the bearing impulse response signals exactly.

This paper investigates the problem of the spectrally compatible waveform design for colocated multiple-input multiple-output (MIMO) radar transmit beampattern formation under peak to average power ratio (PAR) and similarity constraints. The waveform is designed by minimizing a weighted summation of the beampattern integrated sidelobe to mainlobe ratio (ISMR) and waveform energy over the space-frequency bands. Since the resulting problem is NP-hard, an approximated primal-dual algorithm inspired by the alternating direction method of multipliers (ADMM) algorithm is proposed. Moreover, the closed-form solution of each primal variable is provided. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach.

This paper jointly designs the transmit and receive beamforming vectors for a multi-mission multiple-input multiple-output (MIMO) radar. The radar searches for potential targets within a prescribed region while tracking multiple targets with known locations. To improve the performance of search mission and track mission, we aim to maximize the transmit energy in the prescribed region and ensure that the received signal to interference plus noise ratio (SINR) of each target is not less than a preset threshold. To tackle the resulting NP-hard problem, we introduce an iterative algorithm based on the sequential optimization procedure. In each iteration, the receive beamforming vectors are first updated by resolving the unconstrained maximization problems. Then, a fractional quadratic constrained quadratic programming (QCQP) is developed for updating the transmit beamforming vector and is solved with semidefinite relaxation (SDR) technique. Numerical simulations verify the convergence performance of the proposed algorithm. The ability of the radar to simultaneously implement the required two tasks is also demonstrated through the synthesized transmit and receive beampatterns.

Particular interest has been shown in the dynamic modeling and the operation of organic Rankine cycle (ORC) systems, which have emerged to harvest energy from low-grade heat sources. In conventional studies corresponding to ORC dynamics, the turbine is generally modeled as a steady-state component, and the efficiency, mass flow rate, and rotational speed of the turbine are less concerned, which may lead to inaccuracy of the system performance during dynamic operations. In this paper, the dynamic model of an ORC system is established, and a comprehensive dynamic turbine model is considered for the first time in such studies. The turbine 1D design and off-design is performed, and the mass inertia and the rotational inertia are also considered in the turbine model. In two operation modes, the dynamic responses of the ORC system to severe disturbance of the heat source parameters are investigated and compared with systems applying conventional steady-state models. Considerable differences have been shown in terms of turbine efficiency (with a maximum relative error of 12.9%), mass flow rate (with a maximum relative error of 8.3%), and net power output of the ORC systems using different turbine models. Furthermore, the use of the dynamic turbine model has extended the settling time and undershoot of the controlled parameter. This study reveals that the dynamic turbine model should be carefully considered in investigations related to ORC dynamics.

A robust transmit beampattern matching synthesis approach is described for a multiple-input and multiple-output radar with manifold vectors perturbation. This synthesis technique minimises the worst-case matching performance between the transmit beampattern and the desired beampattern (in a least absolute deviations sense), through designing the waveform covariance matrix. Also, the resulting minimax problem can be translated into a convex problem is showed. Finally, simulation results verify good performance of the proposed robust transmit beampattern synthesis approach.

This paper designs waveform for dual-functional multiple-input multiple-output (MIMO) radar-communication system. Reducing multi-user interference (MUI) energy can improve the sum-rate of communication, while a proper transmit beampattern can improve the target detection performance of radar. Considering the above facts, a weighted objective function is developed to design dual-functional waveform, which suppresses the MUI energy and makes the synthesized transmit beampattern approach to our desire. Besides, similarity and constant modulus constraints are enforced to ensure the pulse compression performance and unimodular property of designed waveform. The resulted optimization problem is quartic and non-convex. To tackle it, we develop an iterative algorithm based on the framework of block successive upper-bound minimization (BSUM). The proposed algorithm, monotonic and convergent, requires for low computational complexity, which benefits from the careful derivation to the upper-bound of objective function. Numerical simulations first analyze the convergence performance of the proposed algorithm and then comprehensively evaluate the performance of the designed waveform in terms of communication sum-rate, transmit beampattern and pulse compression performance.

This paper discusses the effect of range migration compensation error on extended target fusion detection, under the distributed high-speed moving platforms. We analyze the linear range migration caused by platforms. More precisely, we consider the situation that, when there exists the range migration compensation error introduced by the Inertial Navigation System (INS) of the platforms. Due to the particularity of extended target, we analyze the performance of fusion detection with the three kinds of target fluctuating models. The influences of compensation error on fusion detection are discussed via simulation results.

This paper investigates the problem of joint optimization of waveform covariance matrix and antenna position for multiple-input multiple-output (MIMO) radar transmit beampattern design. Since the formulated optimization problem of minimization of the mean-square error (MSE) between the designed transmit beampattern and the desired beampattern with respect to waveform covariance matrix R and antenna position p is NP-hard, an iterative method is devised to tackle the resulting problem. Specifically, we first optimize R by the semidefinite quadratic programming (SQP) algorithm for a fixed p, and then update p using the alternating direction method of multipliers (ADMM) method for a fixed R. Finally, numerical simulations demonstrate that the effectiveness of the proposed method.

In this paper, we present a resource-awareness decentralized colocated multiple-input multiple-output radar network for multiple targets tracking. Specifically, we develop a distributed particle filter which incorporates the scheduling of radars. Taking posterior Cramer-Rao lower bound as performance metric, we model the scheduling and power allocation problem of the radar network as a sparse optimization problem. Making use of the sparsity of the solution, the scheduling and power allocation performs jointly. We investigate the decomposable structure of the optimization problem and conduct a decentralized technique to solve it iteratively. We verify the effectiveness of the proposed decentralized radar network with the joint scheduling and power allocation (JSPA) scheme by simulation. The resource utilization is adaptively adjusted according to the states of targets and the performance demand.

This paper investigates the problem of the spectrally compatible waveform design for multiple-in multiple-out (MIMO) radar transmit beampattern formation, subject to peak-to-average-power ratio (PAR) and waveform similarity constraints. Since the formulated optimization problem of minimizing the Integrate Sidelobe Level (ISL) and the waveform energy of the stop-band frequencies is NP-hard, an auxiliary variable is first introduced to modify the non-convex problem into a bi-quasiconvex problem, and then the approximated alternating directions method of multipliers (A-ADMM) algorithm is proposed to tackle the resulting bi-quasiconvex problem. Finally, numerical results are presented to evaluate the effectiveness of the proposed algorithm.

In this paper, a novel approach is proposed to design the transmit waveform for multiple-in multiple-out (MIMO) radar. In practical applications, we usually need to design the transmit beam pattern to approximate a given transmit beam pattern and minimize the cross-correlation sidelobes via designing transmit waveforms for MIMO radar. In this work, we propose a one-step method to obtain the transmit waveform. We first formulate our problem as a nonconvex fourth order polynomial optimization problem subject to the energy constraint, and then we propose a distributed convex optimization technique known as alternating direction method of multipliers (ADMM) algorithm to sovle it. Finally, numerical results are presented to demonstrate the effectiveness of our devised approach.

In this paper, we investigate the location and velocity joint estimattion performance for distributed radars on moving platforms, each platform is equipped with phased array radar. The distributed radars system can be inplemented as non-coherent MIMO radar. Firstly, this paper presents maximum likelihood estimation of location and velocity, and then the Cramer-Rao bound for location and velocity joint estimation are derived. We analyze the influnce of the signal bandwith and observation time on estimation performance. Simulation results are provided to verify the correctness of Cramer-Rao bound derivation.

The paper considers the problem of how to simultaneously estimate the direction-of-arrival (DOA) of a source signal and the phase error of a uniform linear array (ULA). We introduce a new method to estimate those parameters for a partly calibrated ULA. As its name suggests, partly calibrated ULA means a array with some of its sensor elements have been calibrated. In particular, our method can be well executed when there is only one calibrated sensor. Firstly, the proposed method reconstructs some sets of data from the array snapshots. According to the subspace theory, a set of linear combination associated with DOA and array phase errors can be extracted with the help of eigenvalue decomposition (EVD). The unknown DOA and sensor phase erros can thus be described by a set of linear equation and its solution can be obtained by least squares (LS) approach. Different from other partily calibrated array based methods, this method can even work well under the condition that the calibrated element is not consecutively located round the reference one. The proposed method is both simple and effective, and simulation comparisons with other algorithms validate its effectiveness.