The appeal of solid propulsion for a lunar lander lies in what engineers call architectural simplicity. A solid rocket motor is essentially a filled pressure vessel: propellant grain, casing, nozzle, igniter. There are no turbopumps, no pressurized feed lines, no valves throttling the flow of fuel and oxidizer, and no cryogenic fluids boiling away in the harsh thermal environment of space. That simplicity translates directly into reliability, and reliability is the currency that matters most when a single ignition opportunity determines whether a mission ends in triumph or in a plume of lunar dust. Mission planners have long been drawn to the idea of a lander that simply lights a solid motor and rides it down.

The catch is equally fundamental. Once a solid motor is ignited, it burns until the propellant is exhausted, and the thrust it produces cannot be throttled, pulsed, or shut down. The vehicle has exactly one chance to get the burn right. This means the ignition time and the resulting burn duration must be predetermined with extraordinary precision, because there is no pilot or autopilot that can ease off the throttle if the trajectory starts to look wrong. Conventional liquid-engine landers, including the Apollo lunar modules and most modern reusable rocket designs, rely on continuous thrust modulation to chase down errors as they develop. A solid-propellant lander forfeits that safety net entirely, which is why the concept has historically been viewed with skepticism for precision landing missions.

Compounding the problem is a subtler enemy: temperature. The performance of a solid propellant is sensitive to the temperature of the grain itself, and the lunar thermal environment—where a landed or orbiting vehicle can swing between searing sunlit heat and deep frigid darkness—induces propellant temperature variations that cause significant errors in the thrust magnitude the motor actually delivers. A motor characterized at one temperature may produce noticeably different thrust at another, and because the burn cannot be modulated, those errors propagate directly into the trajectory. The Inha team identified this thrust uncertainty as the critical failure mode that conventional open-loop guidance, which simply executes a precomputed trajectory, cannot overcome.

The researchers’ answer is to treat the powered descent as a sequential convex programming problem, a class of optimization techniques that has become the workhorse of modern aerospace trajectory design. Convex programming, popularized for planetary landing by the landmark Mars powered-descent guidance work of Behçet Açıkmeşe and colleagues, has the crucial property that the optimization problem can be solved rapidly and reliably to a global optimum, making it suitable for onboard, real-time computation. The lunar lander problem, however, is not naturally convex: fixed-thrust operation and vertical landing constraints introduce complications that must be carefully reformulated. The Inha framework incorporates these critical flight conditions directly, shaping the optimization so that the resulting trajectory respects the physical realities of a solid motor burn and the demanding attitude requirements of a vertical touchdown.

The truly novel contribution, though, is the closed-loop replanning scheme built on top of that optimizer. Rather than trusting the precomputed trajectory, the lander continuously estimates its actual thrust in flight, comparing how fast it is accelerating against how fast it should be. Because the motor’s thrust cannot be changed, the guidance cannot fix errors by adjusting the engine—but it can adjust everything else. The onboard algorithm periodically re-optimizes the entire remaining trajectory, shifting the ignition timing, reshaping the descent profile, and re-targeting the terminal conditions so that the vehicle, burning exactly as it must, still arrives at the surface with the right velocity and attitude for a soft landing. In effect, the software trades flexibility in thrust for flexibility in timing and geometry, re-solving the whole problem every time the estimate of the motor’s behavior changes.

The numerical simulations reported in the paper show that this approach works. Under thrust deviations of up to 1.5 percent—a level that would produce unacceptable landing errors under an open-loop baseline—the replanning algorithm successfully mitigated the severe thrust errors, ensuring precise terminal convergence and reliable soft-landing performance. The horizontal landing error was constrained to within a few meters of the target, a figure that would enable pinpoint landing rather than merely landing somewhere safe within a broad ellipse. For missions targeting specific scientific sites, lava tubes, polar ice deposits, or pre-positioned infrastructure, the difference between a kilometer-scale and a meter-scale landing footprint is the difference between a feasible and an infeasible mission.

The work sits within a rich lineage of lunar descent guidance research stretching back to the Apollo era, when the zero-effort-miss and zero-effort-velocity guidance concepts first put astronauts on the Moon, and to the foundational optimal thrust-programming analyses of the 1960s. What distinguishes the new framework is its marriage of that classical problem—soft landing under a fixed, unthrottleable thrust profile—with the modern machinery of convex optimization and in-flight estimation. Earlier studies had explored solid-propellant arrangements for the lunar soft-landing problem and hybrid rocket alternatives, but the closed-loop, estimation-driven replanning approach addresses the thrust uncertainty problem in a way those open-loop concepts could not.

The implications extend beyond any single lander design. Solid propulsion’s simplicity makes it attractive for small, low-cost lunar missions, including the growing wave of commercial and academic payloads riding on commercial lander platforms, where every valve, pump, and pressurant tank removed from the design is weight, cost, and failure modes eliminated. A guidance framework that can guarantee meter-class accuracy with a motor that behaves like a firework—light it once and it burns—could open precision landing to mission classes that could never afford the complexity of a throttleable liquid engine. The research was supported by funding from the Korea AeroSpace Administration, reflecting national investment in lunar landing capability.

There remain, of course, the usual caveats that separate simulation from flight. The results are numerical, and translating a real-time optimizer into flight software that runs on radiation-tolerant hardware, fuses real sensor data, and survives the communication blackouts and environmental surprises of an actual descent is a formidable engineering task in its own right. But the core insight is durable and, in its way, elegant: when the engine cannot adapt, the plan must. By making the trajectory itself the adaptive element—continuously re-optimized onboard as the true thrust of the motor reveals itself—the Inha team has shown that the simplest propulsion system in the rocketry catalog can be guided to a landing as precise as any throttled engine could achieve. For the next generation of lunar explorers, the smartest part of the spacecraft may matter more than the most sophisticated one.

Subject of Research: Real-time trajectory optimization and closed-loop replanning for a solid-propellant lunar lander during powered descent

Article Title: Real-Time Landing Trajectory Optimization of a Lunar Lander with Solid Propellant

Article References: Seo, J.-M., Kim, H.-J., & Ryoo, C.-K. (2026). Real-Time Landing Trajectory Optimization of a Lunar Lander with Solid Propellant. International Journal of Aeronautical and Space Sciences. https://doi.org/10.1007/s42405-026-01247-y

Image Credits: AI Generated

DOI: 10.1007/s42405-026-01247-y

Keywords: lunar landing, solid propellant, trajectory optimization, sequential convex programming, real-time replanning, powered descent guidance, thrust estimation, soft landing, spacecraft guidance, convex optimization, lunar exploration, aerospace engineering