As the number of spacecrafts performing orbital maneuvers has been increasing, the timely detection of the maneuver along with post-maneuver orbit characterization has become crucial for space situational awareness. In this paper, a new algorithm to detect and characterize maneuvering spacecrafts is proposed based on the interacting multiple model estimation. It is assumed that the types of possible maneuvers are finite and each maneuver is characterized by resulting change in the orbital elements. Under the assumption, the maneuvering spacecraft is modeled as a jump Markov nonlinear system having multiple modes, each of which describes the spacecraft’s motion subject to the corresponding orbital elements. Through the interacting multiple model estimation, the mode probabilities which represents how likely each mode is currently in operation are computed. The maneuver detection and the post-maneuver orbit characterization are then performed simultaneously by identifying the mode with the highest mode probability. The effectiveness of the proposed algorithm is demonstrated through numerical simulations.

Interacting Multiple Model Estimation for Spacecraft Maneuver Detection and Characterization

As recently demonstrated, compressive sensing (CS) is potential in exact recovery of an unknown sparse signal from very limited samples. In this paper, sub-Nyquist sampling jamming against inverse synthetic aperture radar (ISAR) imaging is presented, where the CS-based algorithm is applied to the high-resolution range profile (HRRP) reconstruction other than the Doppler profile reconstruction. The reconstruction of moving targets’ HRRP through CS-based matched filtering algorithms shows that the sub-Nyquist sampled jamming signals, formed by the under-sampled radar signals in scatter-wave jamming configuration, provide a capability of deception jamming. The finally reconstructed ISAR images show that the deceptive false-target images retaining the real target information will be induced. Hence, the rational utilization of sub-Nyquist sampling jamming can generate vivid decoys in ISAR countermeasures. Experimental results of the scattering model of the Yak-42 plane are used to verify the correctness of the jamming idea.

Sub-Nyquist Sampling Jamming Against ISAR With CS-Based HRRP Reconstruction

An anomaly hypothesis testing technique using the minimum-fuel control distance metric is extended to incorporate non-Gaussian boundary-condition uncertainties and employ binary hypothesis testing. The adjusted control distance metric uses Gaussian-mixture models to model non-Gaussian boundary conditions, and binary hypothesis testing allows inclusion of anomaly detection thresholds and allowable error rates. An analogous framework accommodating Gaussian-mixture models and binary hypothesis testing is developed using Mahalanobis distance. Both algorithms are compared using simulated and empirical satellite maneuver data. The north–south station-keeping scenario shows control distance to be less sensitive with increased uncertainty than Mahalanobis distance but more consistent with respect to observation gap duration, a trend which is corroborated using available real-world data. The same consistency with respect to observation gap is observed in East–west station-keeping while also showing the control dis...

Control Cost and Mahalanobis Distance Binary Hypothesis Testing for Spacecraft Maneuver Detection

The micromotion dynamics and geometrical shape are considered to be essential characteristics for exoatmospheric targets discrimination. Many methods have been investigated to retrieve the micromotion features using radar signals returned from targets of a given shape. We explore a way of jointly estimating micromotion dynamics and geometrical shape parameters from the infrared (IR) signals of targets in remote detection distance. It is found that the micromotion dynamics of the target would induce a periodic fluctuating variation on the IR irradiance intensity signature. In addition to the micromotion characteristics, the fluctuation could also reflect target structure properties, which offer a possible clue in extracting the features of micromotion dynamics and geometrical shape. Thus, the data model of target IR irradiance intensity signatures induced by micromotion patterns including spinning, coning, and tumbling is developed, and a method of parameters estimation based on joint optimization analysis techniques is proposed. Experimental results demonstrated that the parameters of target micromotion dynamics and geometrical shape can be effectively estimated using the proposed method, if the input signature contains multiple dominant frequency components.

Micromotion dynamics and geometrical shape parameters estimation of exoatmospheric infrared targets

Micro-Doppler (MD) caused by the motion of the ballistic missile can contribute to successful recognition of the ballistic missile. Considering the real observation scenario. This paper proposes a method to derive the MD image of the ballistic missile by applying the range-Doppler algorithm (RDA) based on the real ∞ight scenario and analyzes the factor for the real-time MD imaging. Simulation results using the ∞ight trajectory constructed using the real target parameter demonstrate that we need a new cost function for phase adjustment and a new method for range alignment. In addition, matched-flltering needs to be performed in the baseband, and a su-cient PRF is required to prevent discontinuity of the MD image. Dechirping of MD and flltering of the random movement are also needed for a clear MD image. Among the various weapons used in the modern battlefleld, the ballistic missile in∞icts the biggest threat due to its high maneuvering speed and low radar cross section (RCS), and thus defending against the ballistic missile is a major issue. Recently, a theory has been developed to explain micro-Doppler (MD) efiect caused by the micro motion of the target and applied for radar target recognition purpose (1,2). In the case of the ballistic missile, three motion components | spinning, conning and nutation | cause MD, and they can be utilized for target recognition in combination with the motion parameter (1,3,4). However, very little research has been reported on its application to the real ∞ight scenario and the factor that needs to be considered for the real-time MD imaging. In this paper, considering the real observation scenario by a radar, we propose a method to extract an MD signature of a ballistic missile engaged in the real ∞ight scenario by applying the range-Doppler algorithm (RDA), which is generally used to form the inverse synthetic aperture radar (ISAR) image (5{8), and analyze various factors for the real-time high quality MD image. For this purpose, we constructed the ∞ight trajectory by using the real motion parameters of a 500km range scud missile conducted a translation motion compensation (TMC). Then, the time-varying MD image was formed by applying the time-frequency transform (TFT). Various simulations were performed by using the obtained MD image to study the requirement for the real-time MD imaging. Simulation results obtained by using a target composed of the point scatter demonstrate that the MD signature can be successfully constructed by using the range-Doppler algorithm. However, a new method for TMC is required for real-time high-quality MD imaging. In addition, matched-flltering (MF) in the baseband is required to form a focused image, and a su-cient PRF is needed to remove discontinuity. The re∞ected signal needs to be dechirped to reduce the required PRF, and a fllter needs to be designed to remove the random movement.

/pdf/micro-doppler-extraction-and-analysis-of-the-ballistic-3sdz1skta5.pdf

Micro-Doppler Extraction and Analysis of the Ballistic Missile Using RDA Based on the Real Flight Scenario

Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two prob- lems into one interrelated problem, and consider them simultaneously under a sce- nario where space objects only perform a single in-track orbital maneuver during the time intervals between observations. We mathematically formulate this integrated sce- nario as a maximum a posteriori (MAP) estimation. In this work, we propose a novel approach to solve the MAP estimation. More precisely, the corresponding posterior probability of an orbital maneuver and a joint association event can be approximated by the Joint Probabilistic Data Association (JPDA) algorithm. Subsequently, the ma- neuvering parameters are estimated by optimally solving the constrained non-linear least squares iterative process based on the second-order c one programming (SOCP) algorithm. The desired solution is derived according to the MAP criterions. The per- formance and advantages of the proposed approach have been shown by both theoret- ical analysis and simulation results. We hope that our work will stimulate future work on space surveillance and maintenance of a space object catalog.

An object correlation and maneuver detection approach for space surveillance

According to the working mode of the ballistic missile warning radar (BMWR), the radar return from the BMWR is usually sparse. To recognize and identify the warhead, it is necessary to extract the precession frequency and the locations of the scattering centers of the missile. This article first analyzes the radar signal model of the precessing conical missile during flight and develops the sparse dictionary which is parameterized by the unknown precession frequency. Based on the sparse dictionary, the sparse signal model is then established. A nonlinear least square estimation is first applied to roughly extract the precession frequency in the sparse dictionary. Based on the time segmented radar signal, a sparse component analysis method using the orthogonal matching pursuit algorithm is then proposed to jointly estimate the precession frequency and the scattering centers of the missile. Simulation results illustrate the validity of the proposed method.

/pdf/precession-missile-feature-extraction-using-sparse-component-3xipa36lf5.pdf

Weidong Hu

Papers

An object correlation and maneuver detection approach for space surveillance

Precession missile feature extraction using sparse component analysis of radar measurements

A novel data association scheme for LEO space debris surveillance based on a double fence radar system

A novel signal processing approach for LEO space debris based on a fence-type space surveillance radar system