Inverse Synthetic Aperture Radar (ISAR) is a mature technique with widely usage for its good performance in the field of target detection and recognition. The classical ISAR technique does not has the ability of offering the height information for a target, just because that the two-Dimensional (2-D) image is the result of projection for a three-Dimensional (3-D) target. Hence, it is inappropriate for the target detection and recognition. In the recently years, many 3-D InISAR approaches have been presented to solve the above problem, and the 3-D images can be yielded by the phase difference for the ISAR received signals of separated antennas^{[1–6]}. The orthogonal dual baseline configuration system is applied widespread to achieve the 3-D reconstruction of the geometry of non-cooperation target due to its simplicity and convenience. The methods via the parameters estimate of rotational motion associated with the three antenna configuration to yield the target 3-D reconstruction with ideal 3-D rotation are proposed in Refs. [7,8]. In Ref. [9], a three receiver ISAR imaging system is presented to yield the 3-D images for a target with complicated movements without the information of target motion. Besides, the 3-D InISAR imaging approach via the time frequency representation is brought forward to construct the 3-D images of targets with complicated movement in Ref. [10].
It is very important that a 2-D ISAR image with high quality should be achieved and the scatterer center should also be extracted accurately, which is helpful to estimate the interferometric phase and the high accuracy 3-D reconstruction of coordinate could be achieved consequently. This requires the long continuous echo signals to achieve it. However, it is not simple in the real applications, especially for the multi-function radar with great difficulty to have a relative long coherent process interval. Generally, there are gaps between available wideband echoes for the ISAR imaging. Furthermore, the phenomena of the loss of received signals randomly often occur in the practice, which leads to the spares aperture available in the 3-D InISAR imaging procedure.
The Compressive Sensing (CS) technique can be adopted to reconstruct the received signal in a sparse aperture with good accuracy. Therefore, the CS technique can still be applying in 2-D ISAR imaging to achieve a high quality ISAR image though the received echoes are in sparse aperture Refs. [11–13]. Then, the CS technique can be used in the domain of 3-D InISAR imaging in the case of sparse aperture Refs. [14–18]. The 3-D InISAR imaging approach via the Bayesian CS is mentioned in Ref. [15]. The novel 3-D InISAR imaging approach with limited pulses for the target with dynamic movement by using the Bayesian CS combined with multi-channel processing is proposed in Ref. [16], and this algorithm obtained a more accurate 3-D ISAR image. Both of these references are aimed at the aircraft targets which have only translational velocity or one-dimensional rotation. The method in Ref. [17] considered 2-D rotation of the maneuvering targets from sparse aperture data, and regard the joint multi-channel InISAR 2-D image formation as a joint-sparsity constraint optimization by effectively incorporating the multi-channel data. The Orthogonal Matching Pursuit (OMP) technique is used for the parameters estimation and scatterer center extraction, and the 3-D geometry reconstruction can finally be obtained by the multi-channel images and chirp parameters. Though the 3-D imaging results are very accurate, the complexity of the process has brought some inconvenience to the imaging.
Here, a new 3-D InISAR imaging approach of ship with dynamic movement with sparse aperture is introduced. Due to the movement of the ship target is a synthetic motion of its translational velocity and 3-D rotation, the first step is to implement the envelope alignment for the echoes by adopting the method in Refs. [19,20]. Then the fast minimum entropy phase correction method in Refs. [21,22] is adopted to achieve the phase correction and reduce the wave difference induced by the three antennas. Different from Refs. [12,13,23] in the direct use of CS method to yield the 2-D ISAR images with high quality in the sparse aperture, we use the high-precision gradient-based algorithm in Ref. [24] to achieve the recovery of echo signals. Many studies have shown that the echo of the ship target in each range unit could be seen as a multi- component linear frequency modulation signal. Hence, after the echoes for the three antennas are all reconstructed, the parameter estimation method is used to yield the 2-D ISAR images of ship with high quality^{[1,25]}. Eventually, the 3-D geometry positions for all the scatterers could be reconstructed by combining the interference phase information of the three images.
The structure for the paper can be illustrated as: the basic signal processing for a ship in 3-D imaging is introduced in Section 2; In Section 3, the reconstruction of sparse signal via the gradient technique is introduced and the high-resolution 2-D ISAR images of ship with dynamic movement are obtained after the Fourier transform is performed directly on the echoes whose frequency slope are compensated. In Section 4, the reconstruction of 3-D geometry of ship in sparse aperture is realized by the interfering procedure for the three 2-D ISAR images. The validity of the novel method in this paper is demonstrated via the simulation result in Section 5, and the conclusion of the paper is shown in Section 6.
2 The Basic Signal Processing of the Ship Target in 3-D ImagingThe 3-D InISAR imaging model of ship with dynamic movement based on the orthogonal double baseline is established as Fig. 1. The initial radar line-of-sight (RLOS) direction of radar A is defined as the Y axis, and the X-axis and the Z-axis are constructed in the direction of horizontal and vertical, respectively. The intersection for the three axes can be illustrated as the origin O. At this point, the radar coordinate system (O, X, Y, Z) is defined successfully. The radar A(0, 0, 0) which has the transmitted antenna and the received antenna is locating at the origin, only as the receiving antennas for radar B(L, 0, 0) and radar C(0, 0, L) are lied on the horizontal and vertical directions, respectively, where L is the length of the two baselines AB and AC. The coordinate system (o, x, y, z) of ship can be constructed via the geometric center o for the target as the origin. Generally, both the ship and radar coordinate systems have different directions.
With the aim to understand the three-dimensional InISAR imaging process more easily, the signal processing process of the single-baseline AB configuration is analyzed with a simple two-dimensional plane XOY as an example, and then the signal processing of the baseline AC is analogous. Fig. 2 is the 3-D InISAR imaging model of ship in XOY plane, and it shows the different positions of the target at different times t_{1} and t_{2} during the imaging time. Although the position of the scatterers on the ship target is constantly changing with the movement of it, the relative position between the individual scatterers does not change.
It is supposed that the radar A transmits the Linear Frequency Modulated (LFM) signal with the form of
where
where
The detailed derivation of
For the purpose of reducing the sampling rate of the echo signal to decrease the difficulty of signal processing, the reference signal with the uniform expression as the echo signal is used for the Dechirp process. The reference signal is
where
where
It is easy to find that the third items in Ref. (8) and Ref. (9) are completely caused by the translation of the ship target, which may bring an obvious impact on the ISAR imaging of the target. So far, there are lots of methods of motion compensation have been presented. Here, the approach in Refs. [19,20] is adopted to eliminate the influence brought by the translation component. Different from the general motion compensation, we use the motion parameters of radar A to compensate radar B and C because of the three ISAR images of A, B and C must be obtained with the same focus center in the 3-D InISAR imaging. After motion compensation, the echo signal of radar A, B and C can be obtained as
where
From Eq. (10) and Eq. (11), it’s easy to know that the first item is used to realize the range compression of the target, and the second item is to achieve the azimuth resolution of all the scatterers. More importantly, the third item whose phase does not change with the time is the essence of 3-D InISAR imaging. The main impact of the fourth item is to make the scatterers appear Migration Through Resolution Cell (MTRC) and the influence could be ignored during the short imaging time under normal circumstances, then the influence caused by the fourth item can be eliminated. The fifth item in Eq. (11) has little impact on the range focus of scatterers and it can be ignored. The last item which is caused by the base station configuration in Eq. (11) is the wave difference of radar A and radar
After the above-mentioned procedure of the echoes, the one dimensional envelope of A, B and C could be obtained through the range compression as
where
For the purpose of achieving the coregistration of the three ISAR images, the method proposed in Ref. [22] is used to estimate the motion angles
Through the above analysis, the image coregistration can be realized by using
The discrete form of one dimensional range profile
s_{gn} denotes the received signal vector for the n-th range unit of radar g with the sparsity performance in the frequency domain. When the received signal is not complete, the method via gradient technique in Ref. [24] can be used to achieve the signal recovery efficiently. The main idea of this algorithm can be described as follows. The missing data are considered as variables, and it can be varied by an iterative method when the minimum value for the convex l_{1} norm based sparsity can be achieved with a reasonable precision. We assume that there two sampling forms for the echoes in Fig. 3 and Fig. 4. One is the Random Missing Sampling (RMS) in Fig. 3 and the other is the Gap Missing Sampling (GMS) in Fig. 4. The RMS mode means that the data of each range bin is missing randomly, and the GMS mode means that the data can be missing in a certain time interval. Use
From Ref. [24], the missing signal recovery will be translated into the following optimization problem
where the components of s_{gn} are
where
It is assumed that the missing sample echo signals of radar A, radar B and radar C can be well reconstructed through the gradient-based algorithm analyzed in the above part, we can still get the form of one-dimensional range profiles of the three radars as Eq. (14) and Eq. (16). For the purpose of getting the 2-D ISAR images of the three radars, it is necessary to carry out the azimuth compression of the last terms in Eq. (14) and Eq. (16). But for the specificity of the ship target, different from the general maneuvering target, the combination of the 3-D rotation and the translation velocity of the ship target causes the distance
Generally, we can find that the echo in each range unit will no longer be a single frequency signal. It will have some flaws if the traditional method by using the Fourier transform to achieve the azimuth resolution is still applied, even in the case of the movement is particularly complex, and it will not be able to imaging. Therefore, the methods that are appropriate to the ship target imaging should be used to get the high resolution in 2-D ISAR images. The method based on the optimal imaging time to realize ship target imaging is proposed in Ref. [28]. Although it is possible to achieve a good focus performance of the scatterers in the azimuth bin, the method has a certain limitation as a result of the short imaging time. The theory of compression sensing is applied to achieve the ship target azimuth high resolution in Ref. [4]. It is difficult to establish the sparse dictionary which needs to estimate the parameters of the target. Besides, if the CS process is applied in the three channels, respectively, the coherence of the three radar echoes will be reduced so that the 3-D InISAR images cannot be achieved. The algorithms via time-frequency analysis to obtain the 2-D ISAR images of ship are proposed in Refs. [29–31]. For the consideration of 3-D imaging, the interference phase that doesn’t change with time needs to be retained. As a result, we need to use a method which can not only preserve the interference phase but also achieve the 2-D ISAR imaging with high quality of ship. Fortunately, many studies have shown that the echo of the ship target can be seen as the superposition of a multi-component LFM signal, which means the components after the second item in Eq. (21) can be ignored. It is appropriate to realize the high azimuth resolution of ship through the parameter estimation technique Refs. [1,25]. Ignoring the high-order component, the 1-D envelope of radar
where
Initialization:
s_{grF} is an empty matrix with the length of M, w=0. Suppose
1. Calculate
2. Find the position of the maximum amplitude of A(m, w), and the value of m is denoted by m_{s}, Compensate the original signal as
3. Let
4. If x(t_{m}) is small enough or w reaches the number of scatterers that need to be found, the loop ends, otherwise return to (1), and let w=w+1.
5. s_{grF} is the result of the azimuthal compression of this range unit.
When all the range units are processed by the above method, the 2-D ISAR image of radar g is
Through a series of processing of the ship target echoes, the high resolution 2-D ISAR images of radar A, B, and C is obtained as Eq. (23). Therefore, the X-axis coordinates for ship could be obtained through the interference processing between A and B. Similarly, the Z-axis coordinates of all scatterers could be recovered with the interference procedure of A and C. In the far field condition, the Y-axis coordinates of the scatterers can be obtained by the distance measurement. For example, for the scatterer p, through the following calculation, its 3-D coordinates
Then X_{p0}, Z_{p0} can be expressed as
Y_{p0} can be estimated by range measurement. Thus, the 3-D reconstruction for the ship could be implemented after all the scatterers are processed by the aforementioned algorithm.
5 Experimental Results 5.1 The establishment of simulation model for ship targetThe simulation model for the ship is established as Fig. 5. There are 22 scatterers of the ship target, the length of the target is 120 m, the width is 40 m and the height is 20 m. Fig. 5(a) is the projection for the ship within x-y plane, Fig. 5(b) is the projection for the ship within y-z plane, Fig. 5(c) is the projection for the ship within x-z plane, and Fig. 5(d) is the 3-D geometry for the ship within x-y-z plane.
The simulated parameters for the ship with complex movement are shown in Tab. 1. We suppose that the ship coordinate system (o, x, y, z) and the radar coordinate system (O, X, Y, Z) have the same direction in each axis at the beginning of imaging.
It is supposed that the translational velocity only has the component of Y-axis, which means v_{X}=0, v_{Z}=0, and v_{Y}=1852×40/3600 m/s≈20.6 m/s. Besides, the distance between the geometry center o of the ship target and radar A is 15 km. The Signal to Noise Ratio (SNR) is supposed to be 20 dB.
5.3 Simulations of the ship target with sparse aperture(1) Experiment 1: Signal missing in two patterns of RMS and GMS
Fig. 6 shows the results of different numbers of random missing samples of the echoes from radar A. Fig. 6 is 2/4 sparse aperture data of the echoes. The results of gap missing samples of the echoes from radar A are shown in Fig. 7. Fig. 7 is 2/4 sparse aperture data of the echoes.
(2) Experiment 2: Comparison of the ISAR images in two patterns of RMS and GMS
The 2-D ISAR images of radar A with 2/4 sparse aperture in the pattern of RMS are shown in Fig. 8. Fig. 8(a) is the result by using the RD technique directly. It can be found that the image of target in Fig. 8(a) is defocused because of the missing echoes. Besides, for the dynamic movement of ship, the Doppler frequency for the edge scatterers during the RD imaging process will be spread like Fig. 8(a). In order to solve the defocus problem of the ISAR image and make all the scatterers achieve good focus performance, the gradient descent algorithm is adopted to reconstruct the missing signals at first, then the method of frequency slope compensation is used instead of RD algorithm to achieve a high-resolution 2-D ISAR imaging of ship, and the result is listed in Fig. 8(b), which provides the basis for the accurate 3-D InISAR imaging. Fig. 9 lists the 2-D ISAR images of radar A in the pattern of GMS, we can have the same conclusion as in Fig. 8.
(3) Experiment 3: 3-D reconstruction for the ship with different sparse apertures in two patterns of RMS and GMS
Fig. 10 and Fig. 11 are the 3-D reconstruction for the ship in the pattern of Random Missing Samples (RMS). Fig. 10 shows the 3-D imaging results for the ship via the algorithm proposed in this paper in 2/4 sparse aperture, it is easy to find that the 3-D InISAR imaging results are basically coincident with the real ship. Fig. 11 is the 3-D reconstruction results for the ship under 1/4 sparse aperture, we can see that the qualities of Fig. 11 and Fig. 10 are almost the same, which means the proposed approach is effective. The 3-D InISAR imaging results for the ship in GMS are given in Fig. 12 and Fig. 13, where Fig. 12 is the result of the target with 2/4 sparse aperture and Fig. 13 is the 3-D image of the target with 1/4 sparse aperture. It can be noted that the image quality in Fig. 12 is slightly better than that in Fig. 13 because of the reconstruct coordinates of some scatterers in Fig. 13 are not completely coincident with true scatterers like Fig. 12, but we the approximate outline of the target can still be identified. From the whole point of view, the performance of the 3-D reconstruction for the ship via the proposed algorithm in 2/4 sparse aperture outperforms that of the target in 1/4 sparse aperture because the former is closer to the true coordinates. Additionally, the 3-D images in Fig. 10 and Fig. 11 are more accurate than those in Fig. 12 and Fig. 13 because the coordinates of the scatterers in Fig. 10 and Fig. 11 are restored more accurately. Hence, it can be found that the proposed algorithm is much useful when the missing data is less and the signal missing is in RMS pattern.
(4) Experiment 4: Comparison experiments of different imaging algorithms of the target with sparse aperture
Fig. 14 shows the results of the target with 2/4 sparse aperture by using the OMP algorithm, where Fig. 14(a) is the 2-D ISAR image, and Fig. 14(b) is the 3-D InISAR image. By compared with Fig. 8(b) and Fig 10, it is evident that the image quality by using the OMP algorithm is not as good as the method presented in this paper. On one hand, the aggregation of the scatterers is relatively poor in Fig. 14(a), on the other hand, the reconstructed scatterers of the 3-D InISAR image in Fig. 14(b) have larger difference from the real points relative to Fig. 10. The results of the target with 2/4 sparse aperture in GMS are given in Fig. 15, by comparing with Fig. 14 and Fig. 15, we can draw the same conclusion as the echoes in RMS, which verifies the effectiveness of our algorithm.
A novel 3-D InISAR imaging technique for the ship with dynamic movement in sparse aperture is proposed. Taking the characteristics of the target into considerate, firstly, we have taken some measures to compensate the received echoes from the three antennas to eliminate the translational component. Meanwhile, the keystone transform is adopted to eliminate the MTRC. Besides, in order to eliminate the wave difference of the three echoes, the image coregistration is adopted in signal processing. What’s more, we combined the gradient-based algorithm and frequency modulation slope estimation to obtain the 2-D ISAR images with high quality and preserve the interference phase under sparse aperture. The 3-D geometry reconstruction for the ship could be achieves by combining the interference procedure results along the two baselines and the distance information. A series of simulations are carried out for the echoes in the two patterns of RMS and GMS, and the numerical results validate the correctness for the novel approach. As a consequence, it can be concluded that the presented technique is suitable for 3-D InISAR imaging for the ship with complex motion in sparse aperture.
AppendixThe calculation of the distance vector
where A_{j} denotes the maximum value of angular amplitude in the radians,
It is assumed that the initial coordinate of scatterer p in radar coordinate system is
where
where
In the far field conditions,
Similarly, we can get
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