Electromagnetic Wave Reradiation TRIZ Cases

See how tapered burner tubes with raised gas ports punched from inside out eliminate burrs, red

Regression on Doppler and azimuth records estimates rigid-body velocity and angular motion accurately even when elevation data is missing.

Vehicle strobe pulses and retroreflector patterns replace heavy radar to guide UAM aircraft to specific landing pads with precise optical navigation.

Marker and vehicle feature scans are combined to calibrate vehicle sensors accurately without guide rails or rollers.

Segmented beam intensities mapped to adjacent receivers let LiDAR detect weak and highly reflective surfaces without saturation.

Time-multiplexed transceiver control lets a LIDAR share ADCs across optical channels, reducing interference while preserving detection accuracy.

Correlation data convolution with Gaussian, Lorentzian, or polynomial functions reduces peak-fitting bias for more reliable LIDAR range and velocity measurement.

Calibration targets at energy supply stations let autonomous vehicles recalibrate perception sensors during automated resupply.

An impedance-matched interface unit lets vehicle radar sit behind fascia with lower wave attenuation, flexible placement, and cleaner exterior styling.

A trench sidewall conductivity layer stabilizes potential gradients in SPAD pixels, reducing charge diffusion and improving temporal resolution.

Piecewise inverse gain and intercept correction linearize compressed lidar ADC signals while avoiding lookup-table power overhead.

By splitting LiDAR detections into upper and lower spaces, the controller filters tunnel features and large vehicles from true obstacles.

External devices and onboard sensors are compared by reliability factors to recalibrate vehicle perception without stopping the vehicle.

Chaotic signal generation and frequency-domain phase analysis improve small-displacement LiDAR accuracy without high-speed modulators or faster ADCs.

Clusters repeated LiDAR returns from homogeneous reflective surfaces to flag specular false positives before driver assistance actions.

Real captured object and background radar data are probabilistically merged to create more realistic autonomous driving simulations.

A delayed-signal differential comparator extracts LiDAR pulse timing and amplitude without high-speed ADCs, reducing pulse pileup and noise sensitivity.

A replica pixel circuit and feedback-adjusted threshold keep pulse width stable under PVT variation, improving ToF photodetection accuracy.

A side sensor placed between dump truck wheels preserves obstacle coverage during steering by avoiding front wheel blockage and blind spots.

By shifting LIDAR scans against a surfel map, this case detects longitudinal bias and improves autonomous vehicle localization.

Backside patterns, concave regions, and guard rings improve photon absorption while reducing premature breakdown in single-photon detection.

A micro-optics LIDAR layout combines isolator, lenses, and chip assembly to cut size and cost while blocking back reflections.

HD map semantics identify static road objects for on-road sensor recalibration, cutting garage returns and improving static-moving object separation.

Overlapping LiDAR views compare object returns to detect blooming artifacts, improving object sizing and vehicle control accuracy.

Rear-facing FMCW LiDAR tracks trailer position and angular motion in real time, enabling corrective action when instability exceeds safe limits.

Interfered distance, speed, and angle ranges are reported to the fusion unit to improve sensor confidence and reduce false alarms.

Separate instruction and status lines keep vehicle targets such as LiDAR active only under valid signal conditions, reducing unintended deactivation.

By splitting tunnel detections into upper and lower spaces, LiDAR can reject false stationary obstacles and avoid unnecessary path changes.

By comparing estimated radar range with lost-track distance, this case detects vehicle sensor degradation despite occlusion and weak returns.

Bias-corrected, ego-motion-compensated LiDAR is locally fitted along vehicle trajectories to estimate road profiles for adaptive suspension control.

Stereo disparity fields and bias-corrected LiDAR improve road surface estimation at long range for obstacle detection and stable navigation.

ICP-based heading consistency checks correct LiDAR track angles with camera and radar cues, improving autonomous vehicle tracking reliability.

A dual-modulator FMCW LiDAR adds a delayed reference beat signal to extend integration time and improve long-range target capture.

Retroreflection monitoring along the laser path detects hard targets and shifts free-space optical systems to a safe state before eye exposure.

Alternating laser and transceiver operation lets LiDAR channels share ADC hardware, reducing complexity and interference while preserving detection precision.

Two lidar sensors compare clustered range returns to suppress fog, snow, and debris reflections while preserving true object detection for vehicles.

A time-delayed differential comparator extracts LiDAR distance and amplitude data without high-speed ADC cost or thresholding errors.

Time-varying pulse dithering creates multiple range hypotheses to separate aliased LIDAR returns and detect objects beyond nominal range.

Two side-mounted radar sensors create overlapping forward coverage for cruise control and cross-traffic alerts while reducing sensor count and failure risk.

A rear-mounted lidar measures trailer angle and trajectory without trailer sensors, reducing blind-spot risk and added failure points.

A balanced spring-fork resonator uses a voice coil and counterweight to cut LiDAR scanning noise, vibration, and power use.

A forgetting-factor update computes mean and variance from streaming radar measurements without storing all data, cutting memory and delay.

A shared processed-data pipeline lets multiple LiDAR processors stream photodetector outputs without shared buffers, cutting latency and storage.

Non-uniform beam expansion and angle-based pulse energy tuning extend LiDAR center range while cutting power use at scan edges.

Projects detected objects from unsynchronized sensors to a common time, improving fusion accuracy without hardware time synchronization.

Separate transmit and receive optical antenna sets with a relay element expand LiDAR field of view while reducing coupling and aberrations.

Dual-polarization gratings capture return beams on both sides of the transmit coupler to improve lidar range and velocity measurement accuracy.

Coherent range-Doppler LIDAR corrects vehicle velocity from point clouds to resolve Doppler ambiguity and improve navigation reliability.

A restoring element lets a vehicle sensor move on impact and return to its calibrated position, reducing injury risk and preserving signal accuracy.

Machine learning separates direct and multipath radar returns, then relocates indirect points to improve autonomous vehicle navigation.

Separating orthogonal return polarizations in a LIDAR pixel boosts SNR and reveals polarization-dependent surface materials for clearer imaging.

Comparing high-energy point-cloud regions across measurements helps distinguish blooming artifacts from real objects and reduce false positives.

Projects detected objects from multiple sensors to a common time using predicted trajectories, improving fusion accuracy for fast-moving targets.

An opaque molded sensor package with exposed active surface and via-based backside routing cuts size, blocks cross-talk, and avoids moisture issues.

Region-specific radar noise estimation and object-type thresholds reveal concealed objects near strong targets while reducing false detections.

When obstacles cover mapped nodes, the vehicle shifts or expands nodes outside the occupied area to keep topological navigation on route.

Variable inter-pulse spacing and staggered channel sequencing cut LiDAR cross-talk while preserving precise real-time 3D distance mapping.

A secondary wide-angle beam redirects transmit light toward the receive path to reduce near-field blind spots and improve depth mapping.

Road-plane estimation and coordinate calibration help vehicle LiDAR maintain recognition accuracy despite sensor posture changes.

Weighted checks on point features and tracking functions identify unreliable LiDAR tracks caused by contamination before vehicle control errors occur.

ML screens a wide radar field while conventional processing verifies the vehicle path, improving braking decisions with lower validation burden.

Airtight sealing, internal heating, and moisture control prevent condensation on safety laser optics in robots moving across temperature zones.

Optical isolators in an integrated LIDAR transceiver suppress back reflections, protecting amplifiers and improving detection accuracy.

FM or PM encoding with a circulator separates return beams to cut crosstalk and back reflections for more reliable range and velocity sensing.

Multiple asymmetric rotating reflectors help distinguish the robot from strong background reflections and improve position and orientation recognition.

Internal counterweight pitch control and onboard navigation let small AUVs map deep sea floor areas without complex external control surfaces.

Selective switching between direct and indirect TOF pixels improves distance sensing across near and far ranges while limiting power use.

Periodic correlation functions with increasing amplitude over distance help ToF sensing resist glare and pixel saturation in far-range measurements.

A mode field expander broadens the beam to match fiber modes, improving LIDAR coupling efficiency and distant target detection.

Multiple laser or radar rays are filtered to isolate platform-surface returns, enabling precise vehicle height and gap adjustment.

Combines wall detection, thermal imaging, laser ranging, and hidden humidity sensing in one compact tool to cut instrument switching and measurement deviation.

Time-delayed signal paths and cross-correlation improve object distance measurement accuracy without requiring a high-speed ADC.

Individual optical attenuators balance amplified local oscillator beam power in LiDAR, improving DSP accuracy and reducing false target detection.

Perpendicular emitter and receiver FOV sizing improves LiDAR channel alignment and keeps distance measurements consistent despite structural variation.

Single-sensor objects are updated directly while multisensor tracks keep filter-based fusion, cutting latency and energy use in vehicle tracking.

Dual-strength bilateral filtering separates depth disambiguation from depth calculation, improving TOF SNR while preserving resolution.

Parallel optical processing units split FMCW LiDAR scanning into smaller matrices to cut attenuation and noise while sustaining high pixel rates.

An opaque wall between the LED and image sensor blocks direct light, shrinking ToF sensor size and power without separate housings.

A conductive strip, pads, and vias spread heat from a suspended waveguide to preserve phase stability and bandwidth in LIDAR.

Histogram skewness corrects mixed reflected-light distortion, improving time-of-flight distance sensing when non-target objects interfere.

Compressive histogram encoding cuts single-photon depth imaging data rates by 1-2 orders of magnitude while preserving depth resolution.

Vehicle speed-based power adjustment cuts distance sensing energy use while preserving reflected-wave sensitivity and accuracy.

Stereo depth guides photon accumulation to selected distance bins, cutting LiDAR power use while improving bin resolution and image quality.

A tapered shaft with circumferential grooves reduces thermal stress during polycarbonate overmolding while improving mirror retention and vibration control.

Channel-specific pulse encoding helps flash lidar reject out-of-channel glare and channel mixing false positives for more accurate ranging.

Motion-compensated point clouds align scattered multi-dwell LiDAR returns to prevent smearing and produce clearer volumetric images of complex motion.

Comparing full and partial light reception reveals indirect light paths, improving optical object detection and distance measurement accuracy.

Two matched signal paths and redundant transmitter groups let a 3D TOF sensor verify failures and support high-integrity object detection.

Dual fisheye lenses with overlapping 180°+ views create a single 360° image, cutting image count and scan time in 3D measurement.

Adaptive light emission and irradiated regions by distance range improve distance image accuracy while lowering ranging power use.

Exposure timing skips near-field dust reflections, reducing lens flare and invalid pixels in time-of-flight distance imaging.

Housing-reflection peaks become a calibration reference, helping LIDAR separate object returns from ambient noise for more accurate ranging.

Multiple concurrent lidar signals illuminate the same region to resolve frequency ambiguity and support long-range, high-refresh distance and velocity data.

Time-divided phase-shifted pixel driving cuts cyclic errors while dispersing current to limit IR drop and EMI in ranging modules.

A fixed matrix mask restructures returned LiDAR light into column patterns, cutting power and data load while preserving detection resolution.

By excluding points outside road-height ranges, Doppler-based displacement estimation stays accurate at low speed and during sudden motion changes.

Closed-loop optical attenuation equalizes local oscillator beam power in LIDAR, improving signal processing accuracy for long-range scanning.

A unified LiDAR pipeline detects sensor type, auto-configures synchronization and data conversion, and cuts integration and maintenance effort.

Pulsed laser timing and DMD diffraction separate fog droplet echoes from object returns, improving camera imaging in rain or fog.

Feature-based sensor fusion estimates a high-confidence localization range when urban street canyons disrupt GNSS signals.

Sparse emitters and wider detector fields cut LiDAR power and motion artifacts while preserving timing resolution for efficient 3D point clouds.

Synthetic abnormal point clouds train an AI model to detect LIDAR faults across varied environments without costly real failure data.

Serial signal selection combines multiple wavelength channels for concurrent LIDAR transmission, increasing data rates and limiting transition interference.