Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications     

Sensor alignment with Earth-centered Earth-fixed (ECEF) coordinatesystem

In this work, we formulate the multiple sensor alignment problem in an Earth-centered Earth-fixed (ECEF) coordinate system. The alignment algorithm maps the sensor measurements to the ECEF coordinates using a geodetic transformation, and attributes the discrepancies in the Earth-referenced system reported by each sensor to the sensor biases. Sensor biases are then estimated using the least squares (LS) technique. Simulated and real-life radar data are used to evaluate the performance of the proposed algorithm. Comparisons are made to those algorithms based on the standard stereographic projection     

Evaluation of multiple radar target trackers in stressfulenvironments

This paper evaluates the performance of multiple target tracking (MTT) algorithms in real-life stressful radar tracking environments. Real closely spaced maneuver radar data, generated by six F-18 fighters and other targets, were collected jointly by the defence departments of Canada and United States to support this practical MTT algorithm evaluation study. A set of performance metrics was defined here to compare the suboptimal nearest neighbor (SNN), global nearest neighbor (GNN), and various variants of the joint probabilistic data association (JPDA) MTT trackers. Results reveal an interesting result that all these MTT algorithms exhibited very close performance. In addition, the weighted sum approach of the PDA/JPDA trackers which are theoretically effective were observed to perform poorly in tracking closely spaced targets. Overall speaking, the GNN filter based on the Munkres algorithm had the best performance in terms of both tracking performance and robustness     

Measurement of middle atmospheric ozone density profile by rocket-borne radiometer onboard KSR-II

KSR-II, a two-stage sounding rocket of KARI was launched successfully at the Korean Peninsula on June 11, 1998. The apogee of the rocket was 137 km. For the ozone measurement, 8-channel UV and visible radiometers were onboard the rocket. The rocket measured an in situ stratospheric and mesospheric ozone density profile over Korea during its ascending phase using the radiometer and transmitted the data to ground station in real time. The maximum ozone density occurs near 25 km. Retrieved profile has a random error (1σ) of approximately 15% for altitude below 20km, 7% between 20-50 km and 10% greater than 50 km. The retrieved data were compared with Dobson spectrophotometer, ozonesonde, and HALOE onboard the UARS. Our results are in reasonable agreements with others.     

Strategies for telecommunications and navigation in support of Mars exploration

The planned exploration of Mars will pose new and unique telecommunications and navigation challenges. The full range of orbital, atmospheric, and surface exploration will drive requirements on data return, energy-efficient communications, connectivity, and positioning. In this paper we will summarize the needs of the currently planned Mars exploration mission set, outline design trades and options for meeting these needs, and quantify the specific telecommunications and navigation capabilities of an evolving infrastructure.     

Cascade-type guidance law design for multiple-UAV formation keeping

A procedure to compute guidance commands for controlling the relative geometry of multiple unmanned aerial vehicles (UAVs) in formation flight is proposed. The concepts of branch, global leader, and local leader/follower are used to represent the whole formation geometry. A positive-definite function defined in terms of the formation error is then introduced and the Lyapunov stability theorem is used to obtain the cascade type guidance law. This scheme leads to the synchronized flight of all UAVs while maintaining formation geometry. The results of a high fidelity nonlinear simulation of a reconnaissance and surveillance mission example are presented to show the effectiveness of the proposed guidance law.     

Space-time registration of radar and ESM using unscented Kalman filter

Space and time alignments are the prerequisites for the successful fusion of multiple sensors. A space-time registration model is proposed to estimate the system biases and to perform time synchronization together for mobile radar and electronic support measure (ESM) systems. A space-time registration model for radar and ESM is first developed, and an unscented Kalman filter (UKF) is proposed to estimate the space-time biases and target states simultaneously. The posterior Cramer-Rao bounds (PCRBs) are derived for the proposed UKF registration algorithm for ESM detection probability less than or equal to one. Theoretical analyses are performed to evaluate the accuracy and robustness of the proposed method. Computer simulations show that the UKF registration algorithm is indeed effective and robust for different radar and ESM tracking scenarios.     

Biased PNG law for impact with angular constraint

A new homing guidance law is proposed to impact a target with a desired attitude angle. It is a variation of the conventional proportional navigation guidance (PNG) law which includes a supplementary time-varying bias. The proposed guidance law does not require a time-to-go estimation and has a simpler form. Analytic conditions for fulfilling the guidance goal are also provided. Simulation results demonstrate that the proposed guidance law has wider launch envelopes than the previous one and shows a good performance even against a maneuvering target     

Performance evaluation of digital beamforming strategies for satellite communications

Smart antennas are becoming one of the promising technologies to meet the rapidly increasing demands for more capacity of satellite communication systems. A main component in a smart antenna system is beamforming. Because of the limitations of analog beamforming, digital beamforming will be employed in future satellite communication systems. We evaluate the performance of various digital beamforming strategies proposed in the literature for satellite communications: 1) single fixed beam/single user, 2) single fixed beam/multiple users, 3) single adaptive beam/single user, and 4) single Chebyshev dynamic beam/multiple users. Multiple criteria including coverage, system capacity, signal-to-interference-plus-noise ratio (SINR), and computation complexity are used to evaluate these satellite communication beamforming strategies. In particular, a Ka-band satellite communication system is used to address the various issues of these beamforming strategies. For the adaptive beamforming approach, subarray structure is used to obtain the weights of a large 2D antenna array, and a globally convergent recurrent neural network (RNN) is proposed to realize the adaptive beamforming algorithm in parallel. The new subarray-based neural beamforming algorithm can reduce the computation complexity greatly, and is more effective than the conventional least mean square (LMS) beamforming approach. It is shown that the single adaptive beam/single user approach has the highest system capacity.     

线切割放电加工助航空客户飞得更高

过去20年里线切割的切割速度几乎增加了5倍,粗加工的直线切割速度可达600mm2/min;对大多数复杂型腔的加工速度较慢,但也可达到约350mm2/min。通过优化粗加工和精加工的策略,变质层几乎为零,同时没有材料或微观结构的变化,放电脉冲的控制特别是脉冲的持续时间和频率是达到最小损伤的关键因素。