Reduction of ambiguity in synthetic aperture radar images

Abstract

A method for operating a synthetic aperture radar (SAR) to obtain SAR echo data for image formation includes the steps of: calculating a nadir ambiguity index for a platform's nadir; determining a frequency sweep direction sequence for successive pulses of a waveform transmitted by the SAR based on the nadir ambiguity index; obtaining a relative phase sequence for the successive pulses of the waveform; and encoding the waveform using the determined frequency sweep direction sequence and relative phase sequence.

Description

[Technical Field]

[0001] This invention relates to the field of imaging using synthetic aperture radar. [Background technology]

[0002] Synthetic aperture radar (SAR) can be used to image an area on Earth (also called a target area) by transmitting a radar beam and recording the return echo from the transmitted beam. SAR systems can be deployed on airborne platforms such as aircraft, as well as on satellites operating from space. Various modes of operation are available for SAR, including strip map, spotlight, ScanSAR (scanning synthetic aperture radar), and TOPSAR (progressive scan SAR for Earth observation).

[0003] Typically, SAR systems transmit radio frequency radiation in pulses and record the returned echoes. The sampled data is stored for processing to form an image. As a result of the pulsed operation of SAR, ambiguity can occur in the image, for example, due to radar echoes backscattered from the nadir or other points outside the target imaging area. These ambiguities can arise because it is difficult to direct the radar beam perfectly to only the target imaging area. In reality, the radar beam has side lobes that also illuminate areas outside the desired imaging area, and radar echoes from these "unknown" areas mix with reflections from the "clear" areas. These echoes of previously and later transmitted pulses scattered from undesirable areas may include the nadir, which is the point directly below the SAR platform (such as a satellite) at its current position. In this case, the SAR image is a combination of the clear image (desired image), a partially focused unknown image, and the nadir.

[0004] One way to overcome the ambiguity problem from regions of unknown range is to increase the size of the antenna in the elevation direction. This narrows the beam width, reduces beam side lobes, and also reduces backscattered signals from the unknown region. However, increasing the antenna size conflicts with the "swap" requirements for the size, weight, and power of small satellites, as well as the need to image a wide range with high resolution.

[0005] Another method that can be used to suppress nadir ambiguity, in particular, is to adjust the pulse repetition frequency (PRF) so that the nadir echo time falls outside the radar's receiving window. In most cases, this is impractical and imposes additional constraints on the PRF, which is already optimized to maximize swath width and minimize the azimuthal ambiguity-to-signal ratio. Furthermore, unknown targets outside the blind range cannot be suppressed by PRF tuning. Instead of applying a fixed or finely tuned PRF, another approach is to use a staggered SAR system where the time range to preceding and succeeding pulses changes continuously, so that ambiguity is placed in different ranges for different range lines. Thus, unknown energy is uncoherently integrated in the Doppler region, resulting in blurring. Unfortunately, the degree of suppression of range ambiguity is very limited with common system parameters, and additional signal processing algorithms are required to achieve isorange sampling in the azimuthal direction.

[0006] Some ambiguity suppression methods focus on transmitting diverse waveforms to allow for the identification and suppression of ambiguity from the return signal, and suppressing the remaining ambiguity by processing the unknown return signal. Below, unless otherwise specified, the term "focusing" is used to refer to statistical or mathematical filtering processes, rather than, for example, optical focusing. An example of filtering is the conjugate convolution of the transmitted and received signals.

[0007] The fundamental idea behind waveform diversity is to gain the ability to "mark" or identify the transmitted pulse from which a particular return signal originates. To achieve this, the system needs to transmit signals with different marks and, accordingly, be able to identify scattered signals. At least three different waveforms have been proposed in the literature: up-and-down chirp (UDC), azimuthal phase coding (APC), and period-frequency (CF).

[0008] UDC (Up and Down Chirp) waveform diversity can be used for nadir suppression, allowing for the extraction of high-quality SAR images. However, energy is not suppressed, but rather blurred in the range direction. This can result in range stripes appearing in the image, especially with targets that exhibit strong backscattering characteristics. Because the signal is blurred rather than suppressed, the total energy of unknown signals is not significantly reduced. In fact, considering the total signal power of a particular target, the suppression capability of UDC can be as low as 3dB for point targets and 0dB for extended targets.

[0009] To overcome some of these problems with UDC, the literature has proposed several post-processing algorithms based on dual-focusing techniques. In these techniques, the raw data is focused according to the unknown region. The image of the unknown region is then thresholded, complex data is suppressed, and higher backscatter is assumed to represent the unknown target. One drawback of this technique is that useful signals may also be lost. The final step is to refocus on the raw data and focus the raw data according to the clear region. However, this algorithm can be computationally intensive, so a less computationally complex post-processing algorithm is desired.

[0010] Another waveform diversity method is APC (Azimuth Phase Coding). In this method, the phases of the transmitted pulses alternate, and the Doppler bandwidth of the clear target signal is shifted outside the processing band. This idea is based on setting the PRF high enough so that the clear and ambiguous Doppler bandwidths of the signal are separated. Unfortunately, this results in a narrow swath width and a reduced azimuth resolution, neither of which is desirable for SAR imaging.

[0011] CF (Cycle Frequency) is a method of generating orthogonal waveforms by periodically shifting the frequency of the transmitted pulses. However, in this case, practical problems such as rapid power drift, hardware implementation complexity, and increased calibration load occur due to the necessary rapid frequency hopping. Furthermore, in SAR systems, there may be limited memory for storing individual waveforms. For example, the TerraSAR-X satellite can only store a maximum of eight different waveforms per acquisition.

[0012] Recently, several efforts have been made to improve nadir suppression performance by combining UDC and APC, but none of these waveforms are designed to address the suppression of ambiguities in both nadir and range in SAR images. Some embodiments of the present invention described below solve some of these problems. However, the present disclosure is not limited to solving these problems, and some of the described embodiments can also solve other problems. SUMMARY OF THE INVENTION

[0013] This summary is provided to introduce, in a simplified form, a selection of concepts that are further described in the detailed description below. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to determine the scope of the claimed subject matter.

[0014] The following is a method of operating a synthetic aperture radar "SAR" to obtain SAR echo data for image formation, where the SAR is mounted on a platform moving relative to the Earth's surface and is directed towards the Earth's surface. This method includes calculating a nadir ambiguity index with respect to the nadir of the platform, determining a frequency sweep direction sequence for consecutive pulses of the waveform transmitted by the SAR based on the nadir ambiguity index, obtaining a relative phase sequence for the consecutive pulses of the waveform, and encoding the waveform using the determined frequency sweep direction sequence and relative phase sequence. As will be explained in more detail below, this encoding by frequency sweep direction and phase can be used to reduce the ambiguity of the SAR image.

[0015] Any of the methods described herein can be implemented to operate a satellite already in orbit, and thus can be implemented in the form of a computing system configured to control the operation of the SAR. The computing system can be mounted, for example, on a platform carrying the SAR system, or can be distributed, for example, between the platform and a ground station.

[0016] Also provided herein is a computer-readable medium including instructions to cause a system to execute any of the methods described herein when implemented in a computing system forming part of the SAR operating system.

[0017] Also provided herein is a SAR system configured to transmit continuous radio wave pulses to illuminate a target area according to any of the methods described herein.

[0018] Also provided are pulsed radio waveforms transmitted from a SAR system mounted on a platform moving relative to the Earth's surface, wherein the waveform is encoded using a frequency sweep direction sequence of continuous radiated pulses, the frequency sweep direction sequence of which varies depending on the ambiguity at the nadir of the platform. The frequency sweep direction sequence of which may vary, for example, depending on the range from the platform to the nadir. The waveforms can be encoded according to any of the methods described herein.

[0019] SAR systems configured to transmit pulse waveforms are also provided.

[0020] The waveform can be encoded using a relative phase sequence for a continuous pulse of radiation, which may vary depending on the ambiguity of points in the unknown region outside the nadir. The relative phase sequence may vary depending on the range from the platform to points outside the nadir.

[0021] In some embodiments of the present invention, a computer-readable medium is provided that, when implemented in a computing system constituting part of a satellite operating system, contains instructions in the form of algorithms that cause the system to perform any of the methods or processes described herein.

[0022] The various aspects and features of the present invention may be combined as appropriate, as will be obvious to experts, or they may be combined with any aspect of the present invention. Embodiments of the present invention will be described with reference only to the following drawings. [Brief explanation of the drawing]

[0023] [Figure 1] This is a schematic perspective view of a satellite in orbit above the Earth. [Figure 2] This is a schematic diagram of satellites operating in space, target areas to be imaged, nadir points, and several unknown areas. [Figure 3a] This is a plot of range-compressed data for clearly defined point targets and point targets within an unknown region. [Figure 3b] This is a plot of range-compressed data for clear point targets and extended targets within an unknown region. [Figure 4a] This is a flowchart illustrating a method for extracting clear images from SAR data using the double focusing method. [Figure 4b] This is a flowchart illustrating a method for extracting clear images from SAR data using the delta focusing method. [Figure 5a] This is a plot of detection points extracted by thresholding the ratio of the target cell to the background in the focused nadir image. [Figure 5b] This plots the sum of the ratios of the test cell to the background in each range bin of the focused nadir image. [Figure 6a] This flowchart shows alternative methods according to several embodiments of the present invention. [Figure 6b] This flowchart shows another alternative method according to some embodiments of the present invention. [Figure 7] This flowchart shows a method for detecting the nadir in SAR data according to several embodiments of the present invention. [Figure 8a] This SAR image shows a mountainous region with strong nadir echoes, an unknown region return, and strong scattering. [Figure 8b] This SAR image shows a blurred top-bottom return in the range direction. [Figure 8c] This is a post-processed SAR image with the apex and décolleté completely suppressed. [Figure 8d] Both are post-processed SAR images with suppressed ambiguity at the nadir and range. [Figure 9a] This graph shows the detection of the nadir from SAR images collected using waveform diversity. [Figure 9b] This is an unknown image of SAR data collected using waveform diversity. [Figure 9c] This graph shows the detection of ambiguity from regions with unknown ranges in SAR images collected using waveform diversity. [Figure 10a] These are SAR images collected using waveform diversity and range striping. [Figure 10b] Figure 10a is a graph comparing the total energy in the range direction and the azimuth angle in the central part with the default image. [Figure 10c] The right-hand section of Figure 10a is a graph comparing the total energy in the range direction and the azimuth angle with the default image. [Figure 11a] This SAR image, taken with a high incidence angle and high pulse repetition rate, shows ambiguity arising from an unknown region. [Figure 11b] The unidentified image in Figure 11a of the SAR image shows that range ambiguity has not been suppressed. [Figure 11c] Figure 11a is an ambiguous SAR image, but range ambiguity has not been suppressed. [Figure 11d] This is a comparison graph of the total energy in the range direction and azimuth angle, compared to the default image in Figure 11a. A common sign is used throughout the diagram to represent similar features. [Modes for carrying out the invention]

[0024] Embodiments of the present invention are described below merely as examples. These examples represent the best way to practice the invention as currently known to the applicant, but are not the only way to achieve it.

[0025] Some embodiments of the present invention provide systems and methods for operating a synthetic aperture radar (SAR) system to acquire images of an area on Earth. For this purpose, the SAR may be mounted on a platform moving relative to the Earth's surface. For example, SAR systems are commonly mounted on satellites. However, the methods and systems described herein are not limited to space and may be performed using aircraft or other suitable platforms.

[0026] In the following description, the term "clear signal" is used to refer to the signal obtained from the target image region, also called the "desired" image area. "Unknown signal" is used to refer to the signal obtained from an unknown region outside the desired imaging area. Unknown signals can mix with clear signals, potentially causing ambiguity in the resulting image. Ultimately, it is desirable to obtain an image of the clear region (target image area) with as little ambiguity as possible. Some of the methods described in this disclosure may include a step of obtaining an image of an unknown region, referred to in this disclosure as an unknown image. This refers to raw SAR data focused on the parameters of the unknown region in order to obtain an image of that region. Unknown images themselves have value because they can provide additional images of another area at a small additional cost. Similarly, a nadir signal refers to the signal returned from a point directly beneath the satellite. The nadir is a special case of an unknown signal, and an image of the nadir region can also be created in the process of obtaining an image of the clear region.

[0027] Figure 1 is a perspective view of a satellite 100 in orbit above the Earth, as an example of a platform that may be used in the methods and systems described herein. The satellite includes a body 110 and "wings" 160. One or more antenna elements may be attached to the wings of the satellite. The satellite 100 further includes a propulsion system 190, shown attached to the body 110 on the opposite side of the solar panels 150. The propulsion system generally includes thrusters 205, 210, 215, and 220 that operate to maintain the satellite 100 in a particular orbit. For example, thrusters 205, 210, 215, and 220 can be used to propel the satellite 100 in a particular direction relative to the Earth. As stated elsewhere, the methods described herein are particularly suited to being implemented in connection with satellite-borne SARs, but are not limited to them.

[0028] The main unit 110 houses a computing system and a control unit, as is well known to those skilled in the art. Figure 1 also schematically shows a ground station computing system 195 configured to post-process received SAR data. Some of the steps of the method described herein can be carried out in the ground station computing system.

[0029] As is known to those skilled in the art, the system operates in a transmission mode in which pulses of radiation are directed toward the Earth's surface, and a reception mode in which radiation reflected from the Earth's surface is received, alternating periodically.

[0030] As is known in this art, creating a SAR image involves transmitting a series of pulses of radio waves to "illuminate" a target scene, and receiving and recording the echo of each pulse. The pulses can be transmitted and the echoes received by a single beamforming antenna. When a SAR is mounted on a mobile platform such as a satellite and moves relative to a target, the antenna's position relative to the target changes over time, and the frequency of the received signal changes due to the Doppler effect. Signal processing of the continuously recorded radar echoes allows for the combination of recordings from multiple antenna positions, forming a synthetic aperture antenna (SAR) to create high-resolution images.

[0031] The area imaged by SAR is called the footprint. The direction along the flight path of the SAR is usually called the azimuth or along-track direction. The direction across the flight path is usually called the range, elevation, or cross-track direction. The direction opposite to the flight path corresponds to the backward direction.

[0032] Referring to Figure 2, we see satellite 100 moving along the azimuthal flight path 200. The satellite is operating in "sidescan" mode, and the area being imaged is to the side of the satellite's flight path, not directly beneath it. This is common with SAR satellites, as bright specular reflections from objects directly beneath the satellite make it difficult to form an image of the nadir region. The shaded area 201 represents the area to be imaged (a clear area). Point 202 is the nadir point, i.e., the point directly beneath the satellite. Areas 204, 205, and 206 are unclear areas where radar reflections from the radar beam lobe may cause ambiguity in the SAR image. Point 203 is a point in unclear area 204 adjacent to clear area 201 where the image is desired. Figure 2 shows satellite 100 operating in conventional stripmap mode. In this mode, as the satellite moves in orbit, the SAR beam is swept along the ground along one swath. However, the examples provided in the current disclosure are similarly applicable to any SAR mode, including Spotlight mode, ScanSAR (Scanning Synthetic Aperture Radar) mode, and TOPSAR (Progressive Scan SAR Topographic Observation) mode. The collected SAR data typically consists of clear areas, unclear areas, and echo signals from the nadir, corresponding to the clear image, unclear image, and nadir image, respectively.

[0033] The examples in this disclosure illustrate the use of improved waveform sequences and waveform diversity. The examples demonstrate the application of up / down chirp waveform coding (UDC) and azimuthal phase encoding (APC) together to suppress both nadir return and ambiguity arising from zones adjacent to the desired imaging area, thereby producing improved SAR images.

[0034] In the case of UDC, instead of transmitting radar pulses at a single frequency, the frequency of each pulse is swept up or down over the duration of the pulse, creating either an "up chirp" or a "down chirp." The signal transmitted by satellite 100 can be described as follows, ignoring the initial phase and power terms:

number

[0035]

number

[0036] Here u and st d Each of the following represents a transmitted signal with up and down chirps, where α is the chirp rate, t is the fast time (or time along the range direction), Tp is the pulse width, and red is the rectangular function.

[0037] A return echo carries either an up or down "signature," indicating whether the return is from a transmitted pulse with an up chirp or a transmitted pulse with a down chirp. For example, an up chirp is transmitted to the imaging area in question. Given the distance to the imaging area and the speed of light, the expected time for a return echo from that area can be determined. However, there may be returns from closer or further areas mixed in with the returns from the desired imaging area. For example, the nadir is much closer, so returns from pulses transmitted later may appear alongside pulses that have traveled to the imaging area and returned. This is an example of ambiguity. By carefully selecting the sequence of up and down chirps, for example, so that all clear imaging returns at a particular point in time are up chirps and nadir returns are down chirps, it becomes possible to filter out the nadir returns using a combined filter.

[0038] The combined filter output of the up-chirp and down-chirp based on the up-chirp reference signal is as follows:

[0039]

number

[0040] In the reverse case (the combined filter output of the up-chirp and the reference signal of the down-chirp), the index function has an inverse phase sign. Therefore, when focusing according to a clear reference signal, the unknown signal becomes out of focus, with the pulse width (2Tp) doubled and the chirp rate halved (α / 2) compared to the transmitted signals (1) and (2). Mathematically, the focusing here is the convolution of the conjugates of the transmitted and received signals. Note that chirps or pulses with either an up or down linear frequency sweep are described as examples, but other types of frequency sweeps can be used similarly according to the current disclosure. Other examples of frequency changes that can be used to identify a pulse include, but are not limited to, nonlinear frequency sweeps, triangular frequency sweeps, parabolic frequency sweeps, or periodic frequency sweeps.

[0041] Figure 3a shows a plot of simulated combined filter outputs comparing clear point targets and unknown point targets, where the transmitted waveform is UDC encoded. Figure 3b shows the same clear point target output using an unknown extended target (an 80-meter long target with a point target at each range sampling interval). The simulation parameters are shown in Table 1 below. It can be seen that the UDC waveform can suppress the point targets by blurring the energy. However, if the backscatter of the target is strong enough, range fringing is expected to appear in the image. In the case of the extended target, it can be seen from 3b that, depending on the size of the target, UDC may not be very effective in significantly reducing the unknown signal. To address this problem, it has been proposed to further modify the waveform as described below.

[0042] [Table 1]

[0043] In the examples provided in this disclosure, UDC is combined with azimuthal phase coding (APC) to more effectively reduce ambiguity originating from the nadir and from undefined regions near the desired imaging area, particularly from the extended target as described above. The basic idea of ​​APC is to shift the Doppler spectrum of ambiguity originating from regions of unknown range so that they can be mitigated during SAR focusing. However, applying APC alone has limitations, such as a narrower swath width and reduced azimuthal resolution.

[0044] The following describes how to calculate the ambiguity index of the platform's nadir and determine the frequency sweep direction sequence based on this nadir ambiguity index. Next, the waveform is encoded using the determined frequency sweep direction sequence and the relative phase sequence (APC) for continuous pulses of the waveform.

[0045] The ambiguity index of the nadir is a positive or negative integer. In other words, different frequency sweep direction sequences or UDC sequences are applied based on the first ambiguity index, which is the ambiguity index of the nadir return.

[0046] Furthermore, a different relative phase sequence or APC sequence can be applied based on a second ambiguity index, for example, the ambiguity index of the unknown region with the strongest reflection (other than the nadir). Since the unknown region with an ambiguity index equal to 1 is usually the region with the strongest reflection, this can be used as the second ambiguity index.

[0047] This method of creating waveform diversity can be used to reduce ambiguity from both nadir reflections and unknown regions near the desired imaging area. If the nadir region is outside the radar echo return range, both the UDC and APC portions of the waveform can be selected based on the ambiguity index (referred to here as the range ambiguity index) of the unknown region where the strongest radar echo is expected to be.

[0048] Determining the frequency sweep direction sequence may involve selecting a frequency sweep direction sequence from a plurality of frequency sweep direction sequences.

[0049] The ambiguity index for the nadir or other regions can depend on one or more of the slant distance, the estimated distance from the platform to the unknown point, and the pulse repetition rate of the waveform.

[0050] The ambiguity index of the unknown point, assuming the Earth is flat, can be expressed as follows:

[0051]

number

[0052] The ambiguity index can be calculated for any point within the nadir and other unknown regions. Referring to Figure 2, line 210 represents the distance to the far end of the clearly imaged area (area 201), which is R in this example. Point 203 is a point in the unknown zone 204, outside of the imaged area 201. The R of point 203 is...n is the distance represented by line 211. In the example, the ambiguity index of point 203 is 1. In fact, the ambiguity index of all points included in the unknown area 204 will be 1. The ambiguity index indicates the order of ambiguity of the range. The strongest ambiguity is usually the ambiguity that occurs from the nadir point 202. Since the unknown area 203 is the zone closest to the clear area 201, the points with an ambiguity index of 1 are most likely to cause the next strongest ambiguity signal (but not always). In this example, the ambiguity index of the points in the unknown area 205 is -1. The ambiguity index of the points within the unknown area 206 is 2. In the case of the nadir point 202, the estimated distance R n is simply the height of the satellite from the ground, as shown by the distance represented by line 212. Below, the symbol N nadir is used to indicate the nadir ambiguity index, and N range is used to indicate the ambiguity index of the points in other unknown areas. The ambiguity index of the nadir point 202 varies depending on the shape of the scene, the distance to the imaged target area represented by line 210, and the distance from the satellite 100 to the nadir point 202 (corresponding to the height of the satellite from the ground).

[0053] Note that the N of a specific point amb varies depending on the position of the imaged target area and may vary for each image acquisition. For example, if the unknown zone 206 is actually the imaged target area, the ambiguity index of the nadir point 202 will be lower than in the example where the area 201 is the imaged target area. The ambiguity index of a point at a certain distance from the satellite may change multiple times during one orbit. This is because the satellite may be tasked to image areas close to or far from the flight path 200 at different parts of the orbit. Intuitively, N ambThis can be considered to indicate the spatial order of unknown and clear regions. The further an unknown region is from a clear region, the greater the N of the unknown region. amb The value will increase. R and R n It is understood that the value of also varies depending on the satellite configuration and mission plan. For example, the antenna elevation angle pattern may have a greater impact on the received signal power than the distance to the target. Therefore, as mentioned above, the strongest ambiguity from unknown regions other than the nadir is usually the ambiguity index N of the range. range This is the number of first (positive) ambiguities with = 1. In this region, the antenna gain is higher than in other unknown regions, even though several other unknown regions are close to the SAR platform. Ambiguities from unknown regions are mainly N range Since it originates from =1, in some embodiments of the present invention, a fixed range ambiguity index (N range >=1) and changing nadir ambiguity index N nadir The waveform diversity is set according to the following. In the latter case, R in Equation 4 n This represents the estimated distance to the nadir.

[0054] As shown in the example below, encoding the waveform with both UDC and APC can suppress both nadir reflections and reflections from other unknown regions. Nadir scattering is a bright target that lies within a few pixels of the SAR image. As a result, the nadir can be defined as a point target (range direction), which can be effectively suppressed using UDC. The remaining ambiguity from regions with unknown ranges can be suppressed with APC.

[0055] Table 2 shows three different waveform sequences combining UDC and APC, and N nadir (First column) and odd numbers N rangeThese are defined for different values ​​in the (second column). In these sequences, the UDC sequence is defined to suppress ambiguity at nadirs, and the APC is defined to suppress ambiguity from the range where the range is unknown. The ambiguity index is limited to 5, but can be easily increased for the same reason.

[0056] [Table 2]

[0057] For example, N nadir Suppose this is calculated to be 4. This means the received signal is shifted by 4 pulses relative to the transmitted signal. In this case, since there is a mismatch in the chirp direction in all of the transmitted and received pulses, nadir suppression works well (see Table 3).

[0058] [Table 3]

[0059] This means that the nadir can be suppressed relatively easily. In the case of a range of unknown magnitude, the strongest reflections usually occur in the region closest to the satellite and the region being imaged, i.e., the range of unknown magnitude where the ambiguity index of the range is 1. When the ambiguity index of the range is 1, all pulses received from the most important unknown magnitude are shifted by 1 relative to the transmitted pulse as follows:

[0060] [Table 4]

[0061] Therefore, for signals with an unknown range, only 2 out of 8 pulses (U and D, phase (π) coding ignored for now) indicate a mismatch with the transmitted signal, while 6 pulses (U and D) indicate a match. Thus, in the examples provided by this disclosure, adding a phase shift of 0 or π helps to further encode the waveform with azimuthal phase coding (or APC) to mitigate ambiguity from the range-ambiguity region. The main idea of ​​APC is to shift the Doppler spectrum of range ambiguity so that range ambiguity is mitigated during SAR focusing operation. To shift the Doppler spectrum by PRF (pulse repetition frequency) / 2, a phase difference of 0, π, 0, π, 0, π, 0, π, ... is required between the transmitted and received pulses. This is N range If the number is odd, this can be achieved if the transmitted up and down chirp is further modulated with phase encodings of 0, 0, π, π, 0 0, π π,... (see Table 4 above). Considering the phase, there are mismatches in 6 out of 8, so post-processing can further identify and remove signals from regions where the odd range is unknown. range If N is an even number and equal to 2, the transmitted pulse can be modulated using APC to 0,0,0,π,0,0,0,π.... range If is equal to 4, the pulse sequence can be modulated to 0,0,0,0,0π, 0.π. Therefore, in this example, N nadir The UDC pattern of the waveform is defined using N range The APC pattern of the waveform is defined using this method. The combined waveform can suppress ambiguity from the lowest point and from the odd or even unknown region.

[0062] The waveform sequences are not limited to those described above. Other sequences are also possible. For example, in the case of up / down chirp (UDC) directional waveform coding, other frequency-direction sequences are possible, such as the following: ●N nadir If the number is odd, the chirp direction sequence will be "UDUDUDUD...." or "DUDUDUDU....". ●N nadir If = 2, the chirp direction sequence will be "UUDDUUDD...." or "DDUUDDUU....". ●N nadir If = 4, the chirp direction sequence will be "UUUUDDDD...." or "DDDDUUUU...".

[0063] Here, "U" stands for "up". Chirp modulation is "D", and down-chirp modulation is "D". Since the power of these ambiguities is usually not significant, higher evens can be ignored. Therefore, determining the frequency sweep direction sequence or UDC may involve selecting a sequence from several possible sequences depending on the nadir ambiguity index.

[0064] Generally, in the case of phase-coded waveform encoding (APC), the phase sequence can be determined by the following equation.

[0065]

number

[0066] Here, φ k is the phase of the k-th pulse. Note that for the first Nabm phase, the starting phase of the waveform can be selected from 0 or π. For example, ●N range If the number is odd, the phase coding sequence can be selected as one of the following: o '0,0,π,π,0,0,π,π...', o 'π,π,0,0,π,π,0,0...' ●N range If the value is 2, the phase coding sequence can be selected as one of the following: o '0,0,0,π,0,0,0,π...' and shifted versions 'π.0,0,0,π,0,0,0...','0π.0,0,0,π,0,0, and '0,0,π.0,0,0,π,0, o 'π,π,π,0,π,π,π,0...' and shifted versions ●When the N range is 4, the phase coding sequence can be selected as one of the following: o '0,0,0,0,0,π,0,π' and shift versions o '0,0,π,π,0,π,π,0' and shift versions o '0,π,π,π,0,0,π,0' and shift versions o 'π,π,π,π,π,0,π,0' and shift versions

[0067] Therefore, to account for ambiguity indices in ranges other than 1, as shown in the example, the relative phase sequence can be determined based on whether the ambiguity index of the range is odd, 2, or 4. One frequency sweep direction sequence can be used for all instances where N nadirs are odd. A larger set of frequency sweep direction sequences can also be used for different even values ​​of N nadirs. Shifts of 0 and π are shown, but the pulse does not necessarily have to be shifted by π; other values ​​such as -π / 2 or π / 2 are also possible. Shifts less than π can also be performed, but the performance in suppressing ambiguity from regions where the range is unknown may not be as good.

[0068] Examples of U-pulses and D-pulses have already been shown in equations (1) and (2). For completeness, the definitions of U+π and D+π can be expressed as follows:

[0069]

number

[0070]

number

[0071] After SAR data is collected, post-processing can be performed, for example, by combining UDC and APC with a frequency sweep direction sequence and / or relative phase sequence selected based on an ambiguity index, to suppress ambiguity in the top, bottom, and range.

[0072] The received raw echo data corresponds to clear regions, unknown regions, and nadirs. Processing may involve extracting nadir data and unknown data using a dual focusing process.

[0073] Figures 4a and 4b show examples of two different post-processing algorithm flows. These figures illustrate a post-processing method that uses dual focusing to remove ambiguity from nadir and areas with unknown range. Generally, SAR data is first processed to detect and suppress nadir, and then the nadir plots are extracted. Subsequently, the data is processed to detect and suppress unknown images and extract images with unknown range. Finally, SAR images of clear regions are extracted. After this processing, nadir ambiguity and ambiguity from other areas with unknown range are virtually eliminated or significantly reduced.

[0074] The method described here is not limited to the sequence of operations illustrated. In particular, the extraction of unknown images may be performed before the extraction of the nadir image, or vice versa.

[0075] First, looking at Figure 4a, the algorithm's input is raw SAR data, which corresponds to data from the nadir, unknown region, and clear region. The first operation 410 focuses the SAR data according to the echo of the nadir, obtaining a focused image of the nadir. The nadir in the image has two major features. First, the signal power is high because the transmitted signal is reflected directly from the object at the nadir. Second, the range deviates only within a narrow region in azimuthal time, and is almost within the same range bin for consecutive azimuthal bins. In operation 412, the nadir is detected and suppressed. To detect the nadir, a range sliding window is applied and the ratio of the cell under test to the background is extracted. The results are shown in Figure 5a, which shows the detection plot in the focused image of the nadir. This ratio is summed for each range bin to detect the nadir, as shown in Figure 5b. The nadir range bin is between 6200 and 6500, and it is clear that plots outside this region may be useful signals.

[0076] Nadir detection has two advantages. First, it is less likely to suppress useful signals. Second, the satellite's ground altitude is measured and can be used for radar altitude measurement. Subsequently, ambiguity of the nadir is suppressed by dividing the data by the time-bandwidth product. Furthermore, the nadir plot is extracted in operation 414.

[0077] In operation 416, SAR data is inversely focused to extract raw SAR data (without nadir echo). Inverse focusing is achieved by applying the conjugate of the filter used to focus the raw data according to the nadir parameter. The sequential application of focusing and inverse focusing preserves phase and amplitude unless suppression is performed. The main challenge in this implementation is to preserve the desired signal that is unaffected by nadir. To achieve this target, focusing and inverse focusing are implemented and the entire bandwidth of the signal is processed. Another challenge is to detect nadir so that only features affected by nadir are suppressed. Focusing includes range compression (RC), range upper limit transition correction (RCMC), and azimuth compression (AC). In this context, RC uses combined filtering and data with a reference pulse number shifted by the ambiguity index of the range relative to the transmitted pulse. RCMC is implemented as phase multiplication. The reference function for AC is estimated using the corresponding range.

[0078] In operation 418, the SAR data is focused with a filter matched to echoes of unknown range. In operation 420, range ambiguity is detected and suppressed. Detecting range ambiguity is a multifaceted problem. The most important feature of range ambiguity is that the signal power is high enough that even images where the target is out of focus appear in the clear image. In this case, the detection problem can be addressed with the Order Statistical Constant False Alarm Rate (or OSCFAR) method [1]. However, OSCFAR can produce false alarms in areas dominated by clear targets. The Cell Averaging (CA) CFAR method [2] can reduce false alarms but comes with the trade-off of increased missed detections. In some embodiments of the present invention, the OSCFAR method is applied. The next step is the CACFAR method. The energy of clear targets is blurred in the range direction while the unknown target is in focus. As a result, instead of estimating the background in the ring, the background is estimated in the range direction, reducing false alarms.

[0079] In operation 422, the unknown image is extracted from the SAR data. Next, the SAR data is refocused in operation 424, and then in step 426, it is focused according to a clear echo of the range (using a filter matched to the clear echo signal), and a clear image without ambiguity of the nadir and range is extracted from the SAR data. As before, inverse focusing is achieved by applying the conjugate of the filter used to focus the raw data according to the unknown region parameter. When focusing and inverse focusing are applied sequentially, the phase and amplitude are preserved unless suppression is performed.

[0080] Figure 4b shows an alternative embodiment of the method described above. Instead of dual focusing, which involves the steps of inverse focusing and refocusing, the method described in Figure 4b replaces these operations with a single focusing operation called “delta focusing.” In other words, in operation 413, the SAR data (unlimited upper bound) is delta focused according to the unknown echo, rather than dual focusing. Similarly, in operation 421, the SAR data is delta focused according to the clear echo, rather than dual focusing, to extract a clear image without ambiguity. The basic idea is that after focusing the raw SAR data according to the nadir parameters (operation 410 in both methods), the data is unfocused SAR data with different configurations for targets in the unknown and / or clear regions, which can then be focused with appropriate parameters to extract the unknown and / or clear SAR images. As a result, using delta focusing reduces the computational load by about half. Waveforms encoded using UDC and APC are compatible with both post-processing methods (i.e., double focusing and delta focusing).

[0081] Figure 6a is a flowchart showing alternative methods according to several embodiments of the present invention. In this case, the raw SAR data is first focused according to a clear echo signal in operation 510. In operation 512, clear images in the SAR are detected and suppressed. The SAR data is then defocused in operation 514 (clear data is gone), and then focused again according to an unknown echo signal in operation 516. This allows unknown images to be extracted from the SAR data.

[0082] Figure 6b is a flowchart showing another alternative method according to several embodiments of the present invention. Here, the raw SAR data is first processed to remove the nadir from the SAR data and obtain a plot of the nadir (operations 502-506), and then inversely focused in operation 508. Subsequently, operations 510-516, the same operations shown in Figure 6a, are performed to obtain an unknown image from the SAR data, but this image does not include the nadir. As before, in another embodiment, the inverse focusing operation 508 and focusing operation 510 in Figure 6b can be replaced with a single delta focusing operation for computational efficiency. An additional unexpected advantage of the disclosed method is that images of the unknown region can be extracted in both processes 6a and 6b. Images of the unknown region provide additional images of a wider area that are useful to the end user of the SAR data.

[0083] Figure 7 is a flowchart showing a method for detecting nadir in SAR data using CACFAR. The first task is to determine the number of guard cells and background cells, and the desired false positive rate. Guard cells are placed adjacent to the cell under test (CUT), before and after it. The purpose of these guard cells is to prevent signal (nadir) components from leaking into the background cells and affecting the accuracy of the noise estimation. In some embodiments of the present invention, the number of guard cells and background cells are set to 5 and 15, respectively, and the desired false positive rate is set to 0.001. However, it is understood that these values ​​may vary depending on the specific requirements of the method. After focusing the SAR data according to the nadir (operation 410 in Figures 4a and 4b), in operation 610, the signal-to-background mean ratio "R" is added for each range index. In operation 612, the nadir peaks are detected, and in operation 614, the width of the nadir is detected. The nadir start (N1) and end (N2) indices, relative to the nadir peak index, are detected using the function shown in Equation 7.

[0084]

number

[0085] Furthermore, as mentioned above, both OSCFAR and CAFAR are applied to detect range ambiguity. In some embodiments of the present invention, for OSCFAR, the desired false alarm rate is set to 0.001, and the noise power is estimated based on the selection of the Nth largest cell, where N is 3 / 4 times the number of SAR data samples. For CACFAR, which is then applied, the desired false alarm rate is the same as for OSCFAR, but the number of guard cells is set to 1000, and the number of background cells is N チャープ It is set to -1000. Here, N チャープ This is the pulse width multiplied by the sampling rate.

[0086] The algorithm for the method described above is derived below for the low squint case, but can be extended to more general cases. A clear target baseband received signal can be approximated as follows:

[0087]

number

[0088] Here, ω r and ωω a This represents the antenna pattern at azimuth and elevation angles. In each case, A0 is the signal amplitude, η is the slow (or azimuth) time, and K a R(η) is the azimuth pulse number, R0 is the range to the target, R0 is the minimum range to the target, and X is the wavelength.

[0089] The first operation 410, which focuses according to the unknown number of pulses, doubles the pulse width while halving the number of pulses in the clear signal. After range compression and azimuthal Fourier transform, the range Doppler data can be expressed as follows:

[0090]

number

[0091] The range cell movement (RCM) term within the range envelope is expressed in terms of the apex-base distance.

[0092]

number

[0093] RCM can be corrected in the range Fourier domain by linear phase multiplication.

[0094]

number

[0095] After RCMC, the signal is described as follows:

[0096]

number

[0097] The final step is azimuth compression relative to the nadir range. In this case, the number of azimuth pulses can be expressed as follows:

[0098]

number

[0099] Finally, the extracted image of the clear target after azimuthal compression can be described as follows:

[0100]

number

[0101] As a result, the signal, after being focused according to the parameters corresponding to the unknown region, is SAR raw data that can be considered as if it were collected with a different configuration. There is no need to defocus and then refocus the signal; instead, it can be focused directly to extract a clear image.

[0102] To validate the proposed range ambiguity suppression method, a series of SAR acquisitions were performed using the ICEYEOy SAR satellite in Espoo, Finland. The imaged scenes include a strong nadir echo, reflections from an unknown region, and a calm water surface expected to correspond to a mountainous area with strong scatterers, as shown in Figure 8a. The SAR image shown in Figure 8a was collected with waveform diversity using a combination of UDC and APC as described in the current disclosure, but post-processing to remove ambiguity from the nadir and other unknown regions has not yet been performed. The mission plan was designed to acquire the nadir line near the center of the swath. The angle of incidence was selected at 37.3 degrees to ensure observation of exaggerated ambiguity from the range unknown region. In the image shown in Figure 8a, it is clear that the clear signal, nadir, and unknown signal are all present in the SAR data. In this example, the nadir ambiguity index is 5.

[0103] Figure 8b shows the same SAR image after processing to suppress nadir reflections and ambiguity from regions with unknown ranges. It was found that nadir reflections and range ambiguity were significantly suppressed. However, there are range fringes in the center of the image that coincide with nadir reflections, and fringes on the right side of the image that coincide with reflections of strong range ambiguity.

[0104] Further post-processing is applied to suppress the remaining range fringing. First, the nadir is detected, as shown in Figure 9a. The estimated nadir is 570005.8m, which is very close to the actual measurement. The strong scatterer labeled as the nadir is suppressed by simply splitting the sample into time-bandwidth products. Next, the raw data without the nadir is focused on to extract a clear image. Figure 8c shows the results of both waveform diversity and post-processing. The range fringing in the center of the image is associated with the nadir and is found to be completely suppressed.

[0105] The next step is to detect and suppress range ambiguity. The unknown image is shown in Figure 9b, and the detection of range ambiguity is shown in Figure 9c. Comparing the detection results with strong scatterers in the unknown image, it was found that the algorithm is very good at detecting targets in the region where the range is unknown, but does not detect scatterers in the clearly defined region as targets. Another observation is that even though the nadir was successfully suppressed in the previous step, there is still some nadir remaining that does not need to be suppressed. This portion can be filtered using the nadir information extracted in the previous step.

[0106] After detecting and suppressing range ambiguity, the SAR image was extracted and is shown in Figure 8d. Qualitatively, it was found that ambiguity arising from the region where the nadir and range are unknown was successfully removed. Unfortunately, quantifying the performance of range ambiguity suppression is not entirely straightforward. Figures 10a, 10b, and 10c show a comparison. Figure 10a shows a SAR image with range stripes. The energy of the unknown target is blurred in the range direction. Therefore, the sum of the energy in the range direction serves as an indicator of the algorithm's performance. Figures 10b and 10c show graphs of the sum of the range relative to the nadir in area 1 of Figure 10a (the area enclosed by the long dashed line and dots), and graphs of the range ambiguity (across azimuthal angles) in area 2 of Figure 10a (the area enclosed by the short dashed line and dots), respectively, compared to the graph of the sum of the range (across azimuthal angles) in the default image. The default image is an image acquired using waveform diversity, but it is the image before the processing step in which nadir and range ambiguity is suppressed using waveform diversity. After processing, it can be observed that nadir ambiguity is suppressed both quantitatively and qualitatively in the region where the desired signal is dominated by nadir returns. Figure 10c shows the performance of range ambiguity suppression. Qualitatively, range ambiguity appears to be suppressed significantly, but background reflections in the region where range is unknown are not low enough to quantitatively verify suppression performance of more than 4 dB using this method.

[0107] To obtain more performance data, another experiment was designed using very high incidence angles and PRF. In this case, the nadir is not within the swath, but the range ambiguity is very strong, as shown in Figures 11a, 11b, and 11c. Clearly, the default image shown in Figure 11a is strongly affected by the range ambiguity. The unclear image shown in Figure 11b proves that the anomaly in the default image is a result of the range ambiguity. As can be seen qualitatively in Figure 11c, the range ambiguity in the desired image is dramatically suppressed. To quantify the power, the sum of the ranges in the region is compared to the default in Figure 11d. The power is indeed suppressed, but the background reflectivity is again very high, preventing the suppression rate from being quantified at more than 8dB, even though this method is clearly working to eliminate the range ambiguity. Finally, strong targets within clear regions can also be suppressed as a result of false alarms.

[0108] In some embodiments of the present invention, a novel method for suppressing nadir and range ambiguity is proposed. This method is based on waveform diversity based on UDC combined with APC and a double focusing technique that includes detection of nadir and range ambiguity. It has been shown that this method not only preserves the desired signal while suppressing the nadir, but also allows detection of the nadir in applications requiring satellite altitude, altitude measurement, etc. Images with unknown ranges are also presented, demonstrating that anomalies in images with non-unknown ranges are a result of range ambiguity. This method is demonstrated and validated with actual SAR data.

[0109] The above describes satellites suitable for performing any of the operating methods described herein. For satellites or other platforms already in orbit, the methods described herein can be implemented by appropriately controlling the satellite, such as from the ground using a suitable computing system. In other words, the SAR operates from the ground, and some of the methods described herein may be implemented in software. Therefore, if the present invention is implemented by a processor in a computing system, a computing-readable medium may be provided containing instructions for operating the SAR in the computing system according to any of the methods described herein.

[0110] Some embodiments of the present invention described herein provide a ground station computing system configured to operate SAR according to any of the methods described herein.

[0111] In any embodiment of the present invention, the satellite may travel within low Earth orbit or be configured to travel within low Earth orbit.

[0112] Any of the computing systems described herein may be combined into a single computing system with multiple functions. Similarly, the functions of any of the computing systems described herein may be distributed across multiple computing systems.

[0113] Some operations of the methods described herein may be performed by software, for example, in the form of a computer program, including computer program code, in a machine-readable form. Therefore, some aspects of the present invention, when implemented in a computing system, provide a computing system-readable medium that causes the system to perform some or all operations of any of the methods of the present invention. The computer-readable medium may be temporary or tangible (or non-temporary) in form, such as a storage medium, including a disk, thumb drive, or memory card. The software may be adapted to run on a parallel or serial processor so that the method steps can be performed in any suitable order or simultaneously.

[0114] In this application, we recognize that firmware and software are valuable commodities that can be traded individually. This is designed to include software that is computed or controlled on “dumb” or standard hardware to perform desired functions. It also aims to include software that “describes” or defines hardware configurations, such as HDL (Hardware Description Language) software that designs silicon chips or configures general-purpose programmable chips to perform desired functions.

[0115] The above embodiments are largely automated. In some examples, the system user or operator can manually instruct some of the actions to be performed.

[0116] In embodiments of the present invention, as otherwise described herein, the system may be implemented as any form of computing and / or electronic system. For example, a ground station may comprise such a computing and / or electronic system. Such a device may comprise one or more processors, which may be a microprocessor, controller, or any other suitable type of processor, for processing computer executable instructions to control the operation of the device in order to collect and record routing information. In some examples, for example, when using a system-on-chip architecture, the processor may comprise one or more fixed-function blocks (also called accelerators) that implement part of the method in hardware (rather than software or firmware). Platform software, including an operating system or any other suitable platform software, may be provided in the computing-based device to enable application software to run on the device.

[0117] Here, “computing system” is used to refer to any device that has the processing power to execute instructions. Those skilled in the art will understand that such processing power can be incorporated into many different devices, and therefore the term “computing system” includes PCs, servers, smartphones, personal digital assistants, and many other devices.

[0118] It should be understood that the above advantages and benefits may relate to one embodiment or to several embodiments. Multiple embodiments are not limited to those that solve any or all of the problems mentioned or that possess the advantages and benefits mentioned.

[0119] Any reference to “item” or “piece” refers to one or more of these items unless otherwise specified. The term “contains” as used herein means to include steps, actions, or elements of the identified method, but such steps, actions, or elements do not constitute an exclusive list, and the method or apparatus may include additional steps, actions, or elements.

[0120] Furthermore, regarding the extent to which the term "inclusion" is used in a detailed description or within the scope of the claims, since the term "inclusion" is interpreted as a transitional term within the scope of the claims, it is intended to have the same inclusiveness as the term "inclusion."

[0121] The attached drawings illustrate an exemplary method. While the method is shown and described as a series of actions performed in a specific order, it should be understood that the method is not limited by order. For example, some operations may occur in a different order than those described herein. Also, some actions may occur simultaneously with others. Furthermore, in some cases, not all operations may be required to implement the method described herein.

[0122] The order of steps or operations in the methods described herein is illustrative, but the steps or operations may be performed in any suitable order, or, where appropriate, simultaneously. Furthermore, steps or operations may be added or replaced, or individual steps or operations may be removed from any of the methods, without deviating from the scope of the subject matter described herein. Further embodiments may be formed by combining an aspect of any of the above embodiments with any aspect of any of the other embodiments described above.

[0123] The above description of preferred embodiments is presented for illustrative purposes only, and it should be understood that those skilled in the art can make various modifications. The above description includes examples of one or more embodiments. Of course, it is impossible to describe each possible modification and alteration of the above device or method in order to describe the above embodiments, but those skilled in the art will recognize that many further modifications and arrangements of various embodiments are possible. Accordingly, the embodiments described are intended to include all such changes, modifications, and variations that fall within the range of the appended claims. List of References [1]Herman Rohling, “Radar CFAR Thresholding in Clutter and Multiple Target Situations,” IEEE Transactions on Aerospace and Electronic Systems, vol. 19, pp. 608-621, 1983. [2]X. Wen, X. Qiu,B.Han, C.Ding, B. Lei and Q. Chen, “A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation”, Sensors 2018, 18, 1454.https: / / doi.org / 10.3390 / s18051454

Claims

1. A method for operating a synthetic aperture radar (SAR) to acquire SAR echo data for image formation, wherein the SAR is mounted on a platform that moves relative to the Earth's surface and is directed toward the Earth's surface, and the method is: A step of calculating a nadir ambiguity index of the platform relative to the nadir before acquiring data from a target region to be imaged, wherein the nadir ambiguity index depends on one or more of the following: the slant distance to the far end of the target area to be imaged, the estimated distance from the platform to the nadir, and the pulse repetition rate of the waveform. Based on the aforementioned nadir ambiguity index, the step of selecting a frequency sweep direction sequence from a plurality of frequency sweep direction sequences for a continuous pulse of a waveform transmitted to a target region imaged by SAR, A step of selecting a relative phase sequence for a continuous pulse of the waveform based on a range ambiguity index, wherein the range ambiguity index depends on one or more of the following: the oblique distance to the far end of the target area to be imaged, the estimated distance from the platform to an unclear point, and the pulse repetition rate of the waveform. A method comprising the step of encoding a waveform using the selected frequency sweep direction sequence and relative phase sequence.

2. The method according to claim 1, wherein the same frequency sweep direction sequence is selected for all instances where the nadir ambiguity index is odd, and a plurality of different frequency sweep direction sequences are selected for different even values ​​of the nadir ambiguity index.

3. The method according to claim 1, wherein the step of selecting a relative phase sequence for a continuous pulse of a waveform includes the step of calculating a range ambiguity index for a point in an unknown region other than the nadir, and determining a relative phase sequence of the waveform based on the calculated range ambiguity index.

4. The method according to claim 3, wherein the determination of the relative phase sequence depends on whether the range ambiguity index is odd or even.

5. The method according to claim 1, comprising the step of processing received raw echo SAR data according to unclear images and clear images, wherein the unclear images are images other than the nadir.

6. The method according to claim 5, further comprising the step of focusing SAR image data using a filter matched to the nadir echo.

7. The steps include detecting the top and bottom of the SAR data, The method according to claim 6, comprising the step of suppressing the nadir from the SAR data.

8. The steps include extracting the nadir from the aforementioned SAR data, The method according to claim 7, further comprising the step of doubly focusing the SAR data according to the unknown echo signal.

9. The step of doubly focusing is, The steps include: inverse focusing using the conjugate of the filter matched to the nadir echo signal, The steps include: focusing the SAR data using a filter matched to the unknown echo signal, and generating a focused unknown image; The steps include detecting an unknown image in focus from the SAR data, The method according to claim 8, further comprising the step of suppressing unclear images that are in focus from the SAR data.

10. The steps include extracting a focused image of an unknown region from the aforementioned SAR data, The method further includes the step of doubly focusing the SAR data according to the aforementioned clear echo signal, The step of doubly focusing the SAR data according to the clear echo signal is: The steps include: defocusing the SAR data, The method according to claim 9, comprising the step of focusing the SAR data using a filter matched to the clear echo signal, and generating a focused, unclear image from the SAR data.

11. The process further includes the step of focusing SAR data using a filter matched to an unknown echo signal to generate a focused image of the unknown, wherein the focusing is performed The steps include compressing the range using a filter that matches the aforementioned unknown echo signal, A step of range cell transition correction, wherein the range cell transition term in the range envelope of the unknown echo signal is a function of the distance to the unknown region, and the step of the above, The method according to claim 6, comprising the step of compressing the azimuth angle with respect to the distance to the nadir, wherein the number of azimuth pulses of the unknown echo signal is a function of the ambiguity index and the distance to the nadir.

12. The steps include detecting an unknown image in focus from the SAR data, The steps include suppressing unclear images that are in focus from the aforementioned SAR data, The steps include extracting in-focus, unclear images from the aforementioned SAR data, The method further includes the step of focusing the SAR data using a filter matched to the aforementioned clear echo signal to obtain a clear, in-focus image, wherein the focusing is The steps include compressing the range using a filter matched to the aforementioned clear echo signal, A step of range cell transition correction, wherein the range cell transition term in the range envelope of a clear echo signal is a function of the distance to the unknown region, and the step of the above, The method according to claim 11, comprising the step of compressing the azimuth angle with respect to the distance to the nadir, wherein the number of azimuth pulses in the distinct echo signal is a function of the ambiguity index and the distance to the nadir.

13. The step further includes doubly focusing the SAR data according to the aforementioned clear echo signal, The step of doubly focusing the SAR data according to the clear echo signal is: The steps include: defocusing the SAR data, The method according to claim 6, comprising the steps of focusing the SAR data using a filter matched to the clear echo signal, and generating a clear, focused image from the SAR data.

14. The method according to claim 5, further comprising the step of focusing the SAR data using a filter matched to the clear echo signal to generate a clear, in-focus image.

15. The steps include detecting a clear, focused image of the SAR data, The method according to claim 13, further comprising the step of suppressing a focused, clear image from the SAR data.

16. The step further includes doubly focusing the SAR data according to the unknown echo signal, The step of doubly focusing the SAR data according to the unknown echo signal is: The steps include: defocusing the SAR data, The method according to claim 14, comprising the step of focusing SAR data using a filter matched to the aforementioned clear echo signal to generate a clear, in-focus image.

17. The process includes the step of focusing the SAR data using a filter matched to the aforementioned clear echo signal to generate a clear, focused image, wherein the focusing is performed The steps include compressing the range using a filter matched to the aforementioned clear echo signal, A step of range cell transition correction, wherein the range cell transition term in the range envelope of a clear echo signal is a function of the distance to the clear region, and the step of the same, The method according to claim 6, comprising the step of compressing the azimuth angle with respect to the distance to the nadir, wherein the number of azimuth pulses in the distinct echo signal is a function of the ambiguity index and the distance to the nadir.

18. The steps include detecting a clear, focused image of the SAR data, The steps include suppressing a clear, focused image from the aforementioned SAR data, The method further includes the step of focusing the SAR data using a filter matched to the unknown echo signal to obtain a focused image of the unknown, wherein the focusing is The steps include compressing the range using a filter that matches the aforementioned unknown echo signal, A step of range cell transition correction, wherein the range cell transition term in the range envelope of an unknown echo signal is a function of the distance to the unknown region, and the step of the above, The method according to claim 17, comprising the step of compressing the azimuth angle with respect to the distance to the nadir, wherein the number of azimuth pulses of the unknown echo signal is a function of the ambiguity index and the distance to the nadir.

19. A computing system configured to control a SAR to operate according to the method described in any one of claims 1 to 18.

20. A computer-readable medium, when implemented in a computing system forming part of a SAR operating system, includes instructions for operating the system according to any one of claims 1 to 18.

21. A SAR system configured to illuminate a target area by transmitting continuous radio pulses according to the method described in any one of claims 1 to 18.

22. A SAR system according to claim 21, mounted on a platform moving relative to the Earth's surface, configured to encode pulsed radio waveforms using a frequency sweep direction sequence and a relative phase sequence selected by the method of claim 1.

Images